Acta Energetica Electrical Power Engineering Quarterly no. 02/2009 by ENERGA SA

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nergetica

02/2009

number 2/year 1

Electrical Power Engineering Quarterly

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ISSN 2080-7570

act

nergetica Content

ENERGY ROADMAPS FOR THE CITY OF GDAŃSK Jerzy Buriak / Marcin Jaskólski

COGENERATION IN A LARGE AND SMALL SCALE Jan Kiciński / Piotr Lampart

LOCATIONAL MARGINAL PRICES (AND RATES) – HARMONIZATION OF MARKET SOLUTIONS WITH NEW DEVELOPMENT TRENDS Roman Korab

POSSIBILITIES OF LOSSES REDUCTION IN MEDIUM VOLTAGE DISTRIBUTION NETWORKS BY OPTIMAL NETWORK CONFIGURATION Aleksander Kot / Jerzy Kulczycki / Waldemar L. Szpyra

REGULATION OF ELECTRICAL POWER MARKET Sylwester Laskowski

DYNAMICS OF FAULT ARC TRAVELING ALONG BUSBARS IN HIGH VOLTAGE SWITCHBOARDS Roman Partyka / Daniel Kowalak

RELIABILITY OF UDP PROTOCOL DATA TRANSMISSION IN ELECTRICAL POWER TELECOMUNICATION SYSTEMS INTERWORKING WITH THE INTERNET Michał Porzeziński / Grzegorz Redlarski

SHOULD k varh METERS BE USED? Zbigniew Szczerba

OPTIMAL VOLTAGE CONTROL IN MEDIUM VOLTAGE POWER ENGINEERING NETWORKS Waldemar L. Szpyra / Aleksander Kot

106

DYNAMICS OF FAULT ARC TRAVELING ALONG BUSBARS IN HIGH VOLTAGE SWITCHBOARDS Krzysztof Wilde

Nowadays, electrical power systems are perceived through the angle of their development. We talk about new, renewable sources of energy – wind, biogas, biomass, the sun – distributed generation, electrical cars or smart grids. Focusing on the future, we, in a sense, forget about the current condition of electrical power systems, including the condition of electrical power grids. Apart from sources of energy, modern electrical power systems also mean thousands of kilometres of various types of electrical power networks of various nominal voltages, thousands of transformers, connecting and measurement devices as well as various types of structures, e.g. dams of water power stations or cooling towers. Many of them are worn out. In many systems, signiﬁcant number of those structures, e.g. electrical power lines is more than twenty ﬁve years old. Today, when it is necessary to extend and develop electrical power grids due to increased electrical energy consumption and due to change of the structure of production in electrical power systems (distributed generation), maintenance of the existing grid infrastructure becomes an equally important task. The maintenance includes diagnosis, which is to detect (predict) threats before a failure occurs. An example referring to diagnosing concrete structures, i.e. electrical power line towers and power structures can be found in this issue of Acta Energetica. Non-investment reduction of energy losses in networks, that is reduction without network extension is another topic referring to both existing and future electrical power lines. The problem is mentioned in two articles. The question whether it is worthwhile measuring the so called power and the product, the so called reactive power and time is worth noting. The values do not have a physical sense although they have physical implications. You are cordially invited to read the articles. Prof. Zbigniew Lubośny Editor in Chief of Acta Energetica

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

Authors / Biographies

Jerzy Buriak Gdańsk / Poland

Marcin Jaskólski Gdańsk / Poland

He graduated from the Faculty of Electrical Engineering of Gdańsk University of Technology (1995). He was awarded the degree of doctor at the Faculty of Electrical and Control Engineering (2001). Now he is employed as an assistant professor in the Chair of Electrical Power of Gdańsk University of Technology. His professional interests include: planning development of energy systems, formulation of optimization models, databases in energy industry..

He graduated form the Faculty of Electrical and Control Engineering of Gdańsk University of Technology (2002). He was awarded the degree of doctor at the same faculty. (2006). Now he is employed as an assistant professor in the Chair of Electrical Power of Gdańsk University of Technology. His professional interests include: integrated modelling of energy system development, renewable and unconventional sources of energy, electrical energy generation in combination with heat.

Energy Roadmaps for the City of Gdańsk

ENERGY ROADMAPS FOR THE CITY OF GDAŃSK Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

1. INTRODUCTION 1.1.

General information The paper presents energy roadmaps for Gdańsk. The term “energy roadmap” is deﬁned as a proposal for energy system undertakings in the given area. And energy system is a set of objects, devices and machinery for generation, processing, transmission, distribution and consumption of energy in all its forms in a given geographical area [9, 10]. Energy roadmaps are presented in three time perspectives: short-term (the year 2012), medium-term (the year 2020) and long-term (the year 2050). The paper is a result of the research carried out under the project PATHways TO Renewable and Efﬁcient energy Systems (PATH-TO-RES), supported by the European Commission programme SAVE Altener Intelligent Energy Europe. Gdańsk is one of cases selected for the research under the project. The other cities are: Göteborg (Sweden), Arnhem, Lochem (Holland), Dunkerque (France) and Valencia region (Spain). 1.2. Geographical borders The city of Gdańsk is situated in the northern part of Poland, on the Gdańsk Bay. A part of Tri-City Landscape Park is situated within its borders. The main area of the region’s development is situated in its southern

Fig. 1. Geographical borders of the city of Gdańsk, source: Google Maps [11]

Abstract The paper presents a strategy and a vision of development of the energy system of Gdańsk. Geographical borders of the analyzed region are shown. Local and global objectives of development of the energy system in the city are described. The key entities involved in the energy system development are speciﬁed. Roadmaps for energy system development are summarized. The sum-up includes presentation of the current conditions of the energy system in Gdańsk, the actions that should be taken up to attain the development strategy objectives, the problems and constraints that can be encountered during the sys-

tem transformation process and a list of key technological options of great signiﬁcance in the future. The roadmaps are considered in three time perspectives: short-term (2012 – actual plan), medium-term (2020 – strategy) and long-term (2050 – vision). Electrical energy and heat demand forecasts were developed for each time perspective. Basic indicators of energy system development in Gdańsk, namely primary energy consumption, ﬁnal energy consumption, CO2 emission indicators and volumes are given at the end of the paper.

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

part. Together with Gdynia and Sopot, Gdańsk makes an agglomeration called Tri-City. The other towns surrounding the agglomeration include: Pruszcz Gdańsk (in the south), Rumia, Reda, Wejherowo (in the north). The city borders are presented in Figure 1. Table 1 presents the basic information about the city of Gdańsk. Tab. 1. Basic information about Gdańsk Surface area ca [km²]

262

Population ca

460 000

General structure of industry

reﬁnery, shipyards, big CHP plant

Basic characteristics of energy system

Dominated by hard coal (commercial CHP plant, industrial CHP plant in the reﬁnery) Natural gas (small CHP plant, local heat plants, individual power boilers, industrial individual power boilers) Modernization of units in CHP plant Outdated and inefﬁcient combined units and coal water boilers in other sectors of industry

Statistical dada database

Statistical Yearbook of Pomeranian Region Statistical Ofﬁce in Gdańsk

2. GLOBAL AND LOCAL OBJECTIVES AND ENERGY SYSTEM DEVELOPMENT PLANS 1.1. Local objectives Local objectives for development of energy system in Gdańsk are presented in Table 2. They were divided by the criterion of time perspective, that is into medium-term objectives and long-term objectives. Medium-term perspective refers to the time needed to complete a given investment (up to 7 years). Long term perspective means the time needed to attain more strategic objectives (usually more than 7 years). Local objectives were specified at the local level, mainly by power plants, generating or supplying electrical energy, heat and natural gas, and by the local authorities, that is by the City Council Administration. Tab. 2. Medium-term and long-term local objectives for development of the energy system in Gdańsk Strategic objective 1. Modernization of municipal system by the new owner, Leipziger Stadtwerke 2. Gasification of oil refining by-products in LOTOS Refinery 3. New generation units powered by natural gas in Elektrociepłownia [CHP plant] Wybrzeże 4. SO2 removal installation in coal units in Elektrociepłownia 2 Gdańsk

Medium-term perspective

Long-term perspective

x x

Internal development plans of Elektrociepłownie Wybrzeże SA and EdF Poland

x x

5. Energy saving in the existing residential districts

6. Construction of heat network for new residential districts

7. Extension of natural gas distribution for heat plants in new residen- x tial districts 8. Construction and modernization of electrical power distribution network x for new residential districts and industrial districts

Comments The project is advanced – a part of the system has been modernized, further modernization is planned Technology provided by Lockheed Martin (USA) as an F-16 “off-set”

Plan till 2030

Internal development plans of Elektrociepłownie Wybrzeże SA and EdF Poland Modernization of buildings: investments are made by private owners and building societies; implementation of regulations on thermo-modernization Plan for electrical energy, heat and natural gas supply in Gdańsk (developed by Energoprojekt Katowice S.A.)

Plan till 2030

see above

Plan till 2030

see above

Energy Roadmaps for the City of Gdańsk

9. Increase of share of biomass x co-combusted with hard coal in Elektrociepłownia Wybrzeże, including Elektrociepłownia 2 Gdańsk 10. Development of electrical system x of public transport

Internal development plans of Elektrociepłownie Wybrzeże SA and EdF Poland

New tram lines, project of the city

11.4% in 2014 12.9% in 2017

Ordinance of Minister of Economy on detailed scope of obligations to obtain and submit for depreciation certiﬁcates of origin, paying replacement fee, purchase of electrical energy and heat generated in renewable sources of energy, and on the obligation to conﬁrm the data on volumes of electrical energy generated in renewable sources of energy (2008)

12. Percentage share of electrical 2.9% in 2009 energy from co-generation based on natural gas combustion in the electrical energy supplied to consumers by distribution company ENERGA-OPERATOR S.A.

3.5% in 2012

Ordinance of Minister of Economy on the way of calculating data in the application for certificate of origin from cogeneration and detailed scope of obligations to obtain and submit for depreciation certificates of origin, paying replacement fee, purchase of electrical energy and heat generated in renewable sources of energy and on the obligation to confirm the data on volumes of electrical energy generated in high efficiency co-generation (2007)

13. Percentage share of electrical energy from co-generation in the electrical energy supplied to consumers by distribution company Koncern Energetyczny ENERGA GROUP 14. Sewage and municipal waste management

23.2% in 2012

see above

11. Percentage share of electrical energy from renewable sources in the electrical energy supplied to consumers by distribution company ENERGA-OPERATOR S.A.

8.7% in 2009 10.4% in 2010

20.6% in 2009

Project of building a new incineration object or gasiﬁcation of waste for production of fuels or electrical energy and heat

As can be seen in Table 2, local objectives for development of energy system of Gdańsk refer mainly to modernization of electrical energy, heat and gas generation and distribution infrastructure. But there are also plans to reduce emission of pollution into air, for example in Elektrociepłownie Wybrzeże. Because of the emission strict standards imposed on power boilers, CHP plants plan building waste gas desulfurization installation. The increased share of biomass combusted in Elektrociepłownia 2 Gdańsk is a result of effective mechanism of promoting renewable energy sources. The plans for new natural gas units will probably be reviewed because of the considerable increase of the price of this fuel.

1.1. Global objectives To provide for a broader context of energy system development, information on global objectives of power industry development was collected and presented in Table 3. The goals set by the European Union (EU) and Poland (PL) were used to specify global objectives in power industry. The objectives were divided according to the criterion of time perspective into medium- and long-term ones.

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

Tab. 3. Medium and long-term global objectives Geographical region Strategic objective

Medium-term perspective

Long-term perspective

Comments

1. Annual 1% reduction of energyintensity

2. Reduction of greenhouse gasses emissions

20% in 2020 against 1990 emission

3. Increase of energy efﬁciency

Reduction of energy Renewable Energy Roadmap consumption by 20% till – Renewable energies in the 2020 against EU projec21st century (EC 10.01.2007) tions till 2020

4. Reaching 20% share of renewable sources of energy in energy balance

20% of total energy consumption in 2020

Renewable Energy Roadmap – Renewable energies in the 21st century (EC 10.01.2007)

5. Reaching 10% share of biofuels in transport fuels sector

10% in 2020

Renewable Energy Roadmap – Renewable energies in the 21st century (EC 10.01.2007)

1. Reaching the objective of the share of electrical energy from renewable sources of energy in the 8.7% in 2009 volume of electrical energy supplied to consumers

11. 4% in 2014

Ordinance of Minister of Economy

2. The objective concerning share of renewable sources of energy in 2020

15% in 2020

Proposal of Directive of the European Parliament and the Council on promoting energy consumption from renewable sources (2008)

3. Reduction of greenhouse gasses emissions till 2020 against the emissions in 2005

+14% in 2020

The European Parliament (with the exclusion of emissions trading system )

4. Objectives concerning share of renewable sources of energy in primary energy consumption

7.5% in 2010

14% in 2020

Development Strategy of Renewable Energy Sector (2001)

5. Energy saving objectives

2% till 2010

9% till 2016

National Plan for Energy Efﬁciency (EEAP) 2007, Ministry of Economy, Warszawa (2007)

Directive 2006/32/EC

Renewable Energy Roadmap – Renewable energies in the 21st century (EC 10.01.2007)

The objectives set at the European level, and then implemented in national regulations, concern three main areas: 1) reduction of greenhouse gasses emissions 2) increase of renewable sources of energy and transport biofuels consumption 3) energy saving, increase of energy efficiency, reduction of energy-intensity. The objectives have a significant impact on development of energy systems in local scale. Buildings must have energy certificates. CHP plants and heat plants operating in a local market are granted CO2 emission allowances and participate in emissions trading system. The share of biomass co-combusted with coal in CHP plants increases, fuels from bio-components appear in petrol stations. It is thus important to translate global strategic objectives into local energy sector development plans, according to the principle “think global, act local”.

Energy Roadmaps for the City of Gdańsk

3. KEY ENTITIES Within the geographical borders of the considered example – the city of Gdańsk – there are various authorities, companies, institutions and organizations that are considered to be the key entities in the development of energy system. Electrical energy generation and distribution companies: • ENERGA GROUP – electrical energy distribution company and distribution system operator (ENERGAOPERATOR S.A.) • Elektrociepłownie Wybrzeże Wybrzeże S.A. – Elektrociepłownia 2 Gdańsk, with Electricite de France as the main shareholder • LOTOS Refinery • Gdańskie Przedsiębiorstwo Energetyki Cieplnej (GPEC), with Stadtwerke Leipzig as the main shareholder • Polskie Górnictwo Naftowe i Gazownictwo (PGNiG) – Gdańsk branch • Pomorska Spółka Gazownictwa Ltd. (PSG) Decision makers, representatives of municipal and regional administration: • City Council Administration of the City of Gdańsk • Marshall’s Office of Pomeranian Region, the authority responsible for development of the region, including energy system, by working out regional strategy for energy sector development. • Key Departments of Marshall’s Office: Department of Environment, Agriculture and Natural Resources, Department of Infrastructure • Regional Governor’s Office • Department of Environment and Agriculture, Department of Infrastructure The role of the supervisory body for environmental protection and use of the environment is played by: • Regional Inspectorate for Environmental Protection (WIOŚ Gdańsk) Investment projects in the form of new energy and environmental protection technologies are supported by: • Regional Fund for Environmental Protection and Water Management in Gdańsk (WFOŚiGW) Consultants: • Energoprojekt Katowice S.A., responsible for developing a plan for electrical energy, heat and gas supply for Gdańsk • Bałtycka Agencja Poszanowania Energii (BAPE), involved in promotion (seminars, fairs, informational campaigns) of renewable energy sources and rational use of energy • Fundacja Poszanowania Energy (FPE), promoting renewable energy sources and rational use of energy (feasibility studies, economic analyses on energy saving and renewable energy sources, education of students, teachers, energy sector staff, local communities) • Instytut Maszyn Przepływowych Polskiej Akademii Nauk (IMP PAN) • Politechnika Gdańska (PG), analyses for electrical energy and/or heat supply companies, research projects on energy planning e.g. PATH-TO-RES, Sustainable Energy for Poland: The Role of Bioenergy (SEP BioEnPol), etc. • other. These entities should play the biggest role in preparing roadmaps for development of energy system. The strategy developed based these roadmaps should be an effect of a compromise, since usually each entity represents its own interests, which are sometimes contrary to the interests of the entities concerned and not always have to lead to an optimal solution from the point of view of the entire system. It is also important to include building societies, real estate owners, etc. into the strategy development process as they play an important role in its implementation.

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

4. DEVELOPMENT ROADMAPS 1.1. The problem This chapter presents the plan of the roadmap for power development of Gdańsk, the results of the research carried out under PATH-TO-RES project. The project is half-way of its implementation, that is why the presented results, inter alia, discussions and consultations with energy companies, are still in progress. The discussed development roadmaps were put in three time perspectives: short-term (current actions and investment plans) – till 2012, medium-term (strategy for development of energy system) – till 2020, longterm (vision of energy system development) – till 2050. In particular, the descriptions include actions in transition periods between individual stages (current and the following one), which was made, respectively, for transition periods, between the current state and shortterm perspective, between the short-term and the medium-term perspective, between the medium-term and the long-term perspective. The presented development roadmap includes projections of electrical energy and heat demand in each of the time perspectives. The sum-up includes also tables of indicators of projected energy consumption and carbon dioxide emission. Furthermore, it was concluded that the main objective of the city authorities is to assure conditions of sustainable development by, in particular, guaranteeing supply of energy and fuels at moderate prices. The energy system of Gdańsk is highly dependent on a well developed centralized heating system with co-generation coal units. The energy and environmental policy of the European Union is focused on reduction of coal share in the fuels balance and it can be expected that it will translate into reduced number of coal units. It is worth noting that the basic strategic objective of providing for supply of energy at moderate prices (necessary for sustainable development of the region), may not be attained, as replacing of coal technologies (with e.g. natural gas ones) projected above can lead to a dramatic increase of energy prices. The other objectives connected with energy system, adopted by the authorities of Gdańsk, are as follows: • development of competition in energy market, that is de-regulation of energy market, but also supporting new investments in energy sector, creating potential for satisfying the growing energy demand • coordination of energy system development in the municipality to provide for consistency with the assumptions of Polish energy policy, long-term national strategy for development of energy sector • supporting combined generation of electrical energy and heat and implementation of the European Commission Directive 2004/8/EC • enhancement of the environment and reduction of industry and municipal environmental impact. The above objectives set the general framework roadmaps for energy development of Gdańsk. That is why the scenarios outlined in the chapters below will be consistent with the general objectives of energy policy. 1.2. Short-term perspective This chapter presents the current situation of the energy system and short-term plans for its development. The year 2012 was chosen as a short-term time perspective because it is the year of the end of the ﬁrst period of regional energy strategy, with special emphasis on renewable sources in Pomeranian Region in 2007–2025 [1], developed by Fundacja Poszanowania Energii in Gdańsk. Transition between the current state and short-term time perspective Descriptions of the actions planned till 2012, divided by energy sectors are presented below: Elektrociepłownie Wybrzeże • diversiﬁcation of fuels • co-combustion of biomass and coal • adapting to new environmental protection regulations • construction of wet desulphurization installation in Elektrociepłownia Gdańsk 2 • installation of ROFA burners in power boilers to reduce NOX emission • tabilization and increase of heat sale in Gdańsk • development of heating system, in particular in southern and western districts of the city

Energy Roadmaps for the City of Gdańsk

• development at the city outskirts small and medium scale sources of combined generation of electrical energy and heat – with the objective of, in longer time perspective, connecting distributed systems to the main heating system Gdańskie Przedsiębiorstwo Energetyki Cieplnej (GPEC) • further modernization of heat mains • development of heating system in many parts of the city • building connections between mains • extension of heating systems of Ciepłownia Osowa and Fundamentowa and Elektrociepłownia Matarnia • withdrawing from using coal in heat plants: Równa and Zawiślańska and building connections between their heating systems and the main heating system • extension of telemetry and telemechanics systems of the heating system • switching from coal to gas in the local heating systems where connecting to the main system is impossible, or where it would be inefficient • replacement of heat distribution centres Pomorska Spółka Gazownictwa • development of medium pressure networks in southern districts of Gdańsk till 2010 • ENERGA S.A. – Branch in Gdańsk • ENERGA S.A. is developing plans for the period of 3 years, the last Framework Development Programme for the period of 2007–2009: • modernization of 110 kV lines of the total length of 38 km • construction of the main feed points: 8 stations of 110/15 kV/kV All energy companies plan to maintain or increase income and share in energy market. On the other hand, they are obliged to meet the requirements specified in government ordinances. Apart from ordinances specifying unit volumes of emissions from energy generation sources there are also ordinances on share of green (renewable), yellow (generated in combination with gas fuel) or red energy (generated in combination with coal) in total electrical energy consumption. Description of heating system This chapter presents the current condition of heating system. In Gdańsk there are six high parameter heating systems. Five of them are managed by Gdańskie Przedsiębiorstwo Energetyki Cieplnej GPEC and one - by UNIKOM company. The total heat power demand is at the level of 717 MW, which is 48% of the city’s demand, and which is at the same time 53% of demand in municipal and public services sector. UNIKOM system is responsible for 0.3% of total city demand, and heat power demand of that system is 5.7 MW. Heating systems were significantly modernized and they are in good condition. But further works are in progress to improve the condition of the system and maintain the already modernized fragments in good shape. Sources: Elektrociepłownia Gdańsk 2, Elektrociepłownia Matarnia, Ciepłownia Osowa are in very ford condition. Ciepłownia UNIKOM is in good technical condition, but heat plants Równa and Zawiślańska are considered to be objects in bad condition, of insufficient efficiency of coal processing into network heat. Only Elektrociepłownia Matarnia uses natural gas, the other use coal or coal mixed with biomass. Heat power reserve in the sources is significant: Elektrociepłownia Gdańsk 2 51 MW Elektrociepłownia Matarnia 3.5 MW Ciepłownia Zawiślańska 4.5 MW Ciepłownia UNIKOM 20 MW In the base scenario it was assumed that instead of construction of a new, central source of heat, the existing power will be used in a more efficient way.

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

The short-term time perspective assumes that the use of biomass will be continued and developed in Elektrociepłownia Gdańsk 2. Biomass will also be used in a few heat plants, e.g.: Fundamentowa, UNIKOM and Zawiślańska. In 2012 ca 110 GWh of “green” heat will be transmitted to consumers, and it will be ca 3% of the total demand for network heat. Table 2 and 3 refer to total demand, not only network heat. Table 2 presents the current structure of demand for heat power for heating purposes and heating water in the city. The next drawing shows projected changes of demand for heat power between the current situation and the year 2010 and 2020. Changes in heat power demand – projection [MW]

Current heat power demand [MW]

Current state – 2020 Current state – 2012

Industry

Municipal sector

Increase for heat power demand (new consumers) Decrease of demand (thermomodernization of buildings)

Other buildings

Table 2. Current structure of demand for heat power in Gdańsk

Table 3. Projection of changes of heat power demand between the current state and 2012 and 2020

In the city, but also in the entire country, the processes of improving thermal insulation of buildings and other thermo-modernization activities are still fairly intensive, which contributes to signiﬁcant reduction of the buildings’ demand for heat power. The demand is partially compensated by new consumers, including the consumers connected to heating systems. Energy saving potential in municipal and services sector is still big. New regulations supporting modernization of residential buildings can provide for keeping the pace of thermo-modernization or even to increase it, and then the presented projections will have to be reviewed. Description of electrical energy system Most of high voltage grids are in good condition, with the exception of certain 110 kV lines, which require modernization urgently. Also some of the main feed points, namely 110kV/15kV stations need to be modernized. However, difﬁculties in connecting new consumers are a real challenge. The condition of the network, its transmission capacity and possibilities of new connections overlap, of course. It is not infrequent, however, that even if the technical conditions are met, a connection cannot be made in a timely manner due to the number of connection applications and exhaustion of the resources allocated for that purpose, which is more frequent in the situation of economic growth and less frequent in the situation of economic decline. Currently, the electrical power demand in Gdańsk is 280 MW. The current demand structure is presented in Table 4. Current electrical power demand [MW]

Multi- family housing

Industry

Public buildings and services

Single-family housing

Table 4. Current electrical power demand in Gdańsk

Energy Roadmaps for the City of Gdańsk

The basic scenario projects an increase of power demand to the level of 330 MW in 2012, and in particular, stabilization or reduction of demand in industrial sectors and increase in the other sectors. Description of natural gas distribution system Pomorska Spółka Gazownictwa is in good shape in terms of its technical conditions and basic assets. It refers in particular to high pressure gas transmission networks. But the network operates at 90% of its transmission capacity, which means that at peak load there is only 10% reserve transmission capacity. The concerns about insufficient transmission capacity forced construction of a new high pressure line of the diameter of 500 mm in the region. The situation in pressure reduction station is not so dramatic as their peak load is only 54% of the nominal capacity. Other remarks The estimations of current heat demand assumed that heat consumption per unit of heated space is below the real demand due to relatively high prices of fuels or network heat. That is why many flats are not heated well enough. Elektrociepłownia Gdańsk 2 provides ca 60% of electrical energy consumed in the city and almost 50% of heat. That is why it would be difficult to minimize the role of energy generated from coal, and it is the problem of not only Gdańsk, but of the whole country. The decision makers traditionally think that fuels - Russian and international coal (e.g. from South Africa, Venezuela), biomass (tree cutting waste, pellets), liquefied natural gas are imported through Gdańsk ports but construction of LNG terminal – big enough for the whole country is planned to be built in Świnoujście, not in Gdańsk. Limiting development of wind power industry due to transmission constraints of electrical power grid is yet another aspect. Connecting wind farms to the system and adapting the system to transmission of power generated in wind farms is very expensive and time consuming. That is why construction of many wind farms will be postponed. Energy from wind farms is and will be insignificant in the energy balance of the city - there are only few farms located in the city suburbs. It is necessary to develop biomass market, for it to gain a big enough potential to deliver enough biomass to the existing and new customers. The following questions are raised in this area: • conflict between using biomass in processes of co-combustion in the existing power boilers and using biomass in modern units with condensing boilers or biomass gasification systems • now modern sources of heat of small and medium power are not able to offer competitive biomass price in comparison with the offers of Elektrociepłownie Wybrzeże, which uses biomass in combined generation of electrical energy and heat. Generating electrical energy from biomass is subsidized by the use of “green certificates”.

1.3. Medium-term time perspective The main expected activities in energy systems of Gdańsk till 2020 are as follows: • construction of gas-steam unit by Elektrociepłownie Wybrzeże (this new investment depends on gas prices forecast, if they are unfavourable – construction of a modern biomass unit is planed); making wet desulfurization installation operational � construction of a new CHP plant in post-shipyard area; the unit would be equipped with CO2 capture installation • increase of competition in heat market as a result of more general use of heat pumps, development of heating systems and construction of local natural gas based sources of heat • popularization of solar collectors, a considerable portion of energy would be used for heating purposes, not only to heat water • savings in energy consumption, in particular due to thermo-modernization of buildings and change of lighting technologies • 5% share of biofuels in road transport • “completing” power processes in LOTOS Refinery as a result of building hydro-cracking installation, integrated gasification combined cycle installation and combustion of remains of oils refining processes • increase of share of modern electrical energy sources: photovoltaic cells, fuel cells, gas engines.

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

The above mentioned activities may result, compared to the present situation, in: • 50% increase of electrical energy production • stabilization and then reduction of CO2 emission • 95% reduction of SO2 emission in the sector of big energy sources. The above mentioned activities take into consideration: • Development plans of LOTOS Refinary and Elektrociepłownie Wybrzeże • Draft assumptions to the plan of heat, electrical energy and gas fuels supply in Gdańsk, Energoprojekt Katowice SA 2005. Description of roadmap for transition from short-term and medium-term time perspective The activities that should be taken up till 2020 for the city energy system to be able to attain the local and global objectives are listed below. The include, inter alia: Elektrociepłownie Wybrzeże, Elektrociepłownia Gdańsk 2, main owner of Electricite de France • fuels diversification • biomass and coal combined combustion • construction of gas-steam unit • adapting to new environmental protection regulations • 2015 - making operational wet desulfurization installation in Elektrociepłownia Gdańsk 2 • stabilization and increase of heat sale in Gdańsk • further development of heating system, in particular in southern and northern districts of the city • development of small and medium scale sources of combined generation of electrical energy and heat at the city outskirts – with the purpose of connecting those scattered systems to the main heating system in the future. Gdańskie Przedsiębiorstwo Energetyki Cieplnej (GPEC) • extension of heating system in many parts of the city • extension of heating systems Ciepłownia Osowa and Fundamentowa and Elektrociepłownia Matarnia • withdrawing from using coal in heat plants: Równa and Zawiślańska, and construction of connections between their heating systems and the main heating system • construction of new source of combined electrical energy and heat generation • construction of multi-energy system with network coolness in the region of Matarnia, Kokoszki Przemysłowe and Kokoszki Mieszkaniowe • further extension telemetry and telemechanics systems of the heating system • transfer from coal fuel to gas fuel in those local heating systems where connection to the main system is impossible or would be inefficient, including installation of new high efficiency boilers in Ciepłownia Balcerskiego • further replacement of heat nodes. Pomorska Spółka Gazownictwa • construction of new high pressure gas pipeline, close to Gdańsk agglomeration and construction of a reduction station near Gdańsk • new gas pipeline for industrial areas of the city: LOTOS Refinery, Port Północny, Elektrociepłownia Gdańsk 2 • extension of medium pressure network in northern districts of the city and further extension of medium pressure network in southern districts of Gdańsk (plans till 2025) ENERGA-OPERATOR Gdańsk Branch • medium-term plans for development of ENERGA GROUP (plans till 2015) – most investments in the period of 2012–2015 • construction of main feed points: eight 110/15 kV/kV stations • plans for after 2015

Energy Roadmaps for the City of Gdańsk

• construction of main feed points: ﬁve 110/15 kV/kV stations • modernization of existing 15 kV networks in many parts of the city. Table 5 presents projection for changes in heat demand in Gdańsk in the period of 2012–2020.

Increase for heat power demand (new consumers) Decrease of demand (thermo-modernization of buildings)

Table 5. Projection for changes in heat demand in Gdańsk in the period of 2012 – 2020

Other remarks It is expected that biomass market will develop and reach a big enough potential to be able to provide biomass to the existing and new customers, including: • increasing biomass share in energy balance of Elektrociepłownia Gdańsk 2 • introducing biomass or increasing its share in heat plants, inter alia, Fundamentowa, UNIKOM and Zawiślańska • biomass for new units with condensing boilers • biomass gasification units. In total in 2020 ca 240 GWh of “green” heat will be transmitted to the customers, which will be ca 6% of total demand for network heat. Construction of a modern gas-steam unit is planned mainly because of the electrical energy market needs. In gas-steam units a considerable bigger portion of chemical energy of the fuel is transformed into chemical energy than in steam units, and deficit of generation capacity is expected in electrical energy market. For the reasons mentioned above, but also thanks to the mechanisms of support, intensive development of wind power generation is planned. The development will take place in the region, but single power stations or small wind farms will be built in the city itself. Development of special urban structures of wind power stations of small capacity is also planned. Vehicles powered by natural gas, biogas or methane-hydrogen mixture (hythane) will be playing a more and more significant role in the public transport sector. It is considered to be a natural stage before fuel cells powered vehicles become more popular. Extension of tram and urban railway connection will be intensified in medium-term perspective.

4.. 4. Long-term perspective The year 2050 was adopted as a long-term perspective. Due to its remote character, further research will have to develop a few roadmaps of sector the development for the city and the region for the period of 2020– 2050. In our opinion, the basic scenario should be based on continued use of coal in big system sources and on distributed sources, using various forms of renewable energy. Additionally, despite plans to intensify activities to increase energy efficiency in previous periods, in this time perspective energy saving will also be a key to the success of the plans. Apart from energy-intensity and distributed energy generation, the base scenario, also proposed “clean” coal technologies are seen as key technologies, e.g.: • dust boilers for supercritical conditions with CO2 capture (e.g. using monoethanolamine) • integrated coal gasification cycles (dry and wet technologies) with CO2 recycling and its compression • coal fired magnetohydrodynamic generators (MHD), also with CO2 capture • fluid pressure boilers, also with CO2 capture

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

The technologies of carbon dioxide capture from combustion gases or coal burning in the atmosphere of previously separated oxygen from the air, and combustion gases recycling and their compression considerably lowers total efficiency of the process of coal conversion into electrical energy, because they are very energyintensive processes (10–20% of the energy produced). Moreover, the use of CO2 obtained in that way is also controversial, even if it is chemically very pure. Pumping CO2 into natural gas and oil deposits is proposed. It would additionally enable increasing the pressure in those deposits and getting more fuels. With extra energy, CO2 can be fixed in synthetic fuels, contributing to saving fossil fuels. The proposed long-term scenario assumes a significant share of electrical energy sources that need to be subsidized now, including: • wind farms (in the region: future generation wind farms, in the city: special low power solutions) • panels of photovoltaic cells (90 GWh) • fuel cells (500 GWh – distributed sources and transport). The forecasted use of fuel cells in transport includes not only hydrogen cells but also cells with conversion of natural gas into hydrogen, biogas and its mixtures with hydrogen. Use of fuel cells in vehicles means also possibility of the so called garage generation only of electrical energy, but also recovery of heat from the cells for municipal purposes. It was also assumed that 80% of the energy generated in the cells will be used for transport purposes, and only 20% for other purposes. The changes in structure of the energy system of the city mentioned above will decide about attainment of the global and local objectives presented at the beginning of the paper. In particular, implementation of this roadmap of development will lead to: • 40–50% reduction of CO2 emissiondue to fossil fuels, not exceeding 40% of total energy for road transport • 110 kWh/(m2/year), as an average value of the indicator of energy demand for heating purposes and heating water. Despite the increase of residential floor space per resident, emission reduction will reach the present level in developed countries of Western Europe. It means doubling the indicator from ca 20 m2 to 40 m2. Description of roadmap for transition from medium-term and long-term perspective The list of example activities is proposed as a sum-up of the above: • construction of integrated gasification combined cycle (IGCC) • application of support mechanisms: • distributed energy sources, including combined generation of electrical energy and heat in public sector, industry, services, powered with natural gas, biogas, hythane (mixture of methane and hydrogen) • microgeneration based on fuel cells • installation of systems of photovoltaic panels of small and medium power • construction of hydrogen distribution networks • construction of hydrogen filling stations (first step – methane compression stations, second step hythane filling stations, which would allow gaining experience and making people acquainted with hydrogen technologies). Other remarks It is observed that in energy sector, like and other sectors of economy, are interested in technologies that promise certainty of profit, that is safe for the investor. Mass application of proven and profitable technologies leads to exhaustion of resources and possibilities of further spread of a given technology. Wind power generation, which is profitable thanks to “green certificates” is an example of energy sub-sectors nowadays. The security of such investments is guaranteed by permanent shortage certificates of origin of energy from renewable sources, that is “green certificates”. It can be expected that after available land has been used to build wind farms, which will have hinder development of that sector, investors will be looking for new niches to invest in energy sector. We think that photovoltaic cell panels will be such a niche. The chances of PV technologies seem to be bigger than those of e.g. fuel cells, as the first ones do not require any fuel supply and storage system. On

Energy Roadmaps for the City of Gdańsk

the other hand, panels require big installation surface areas per unit of the energy generated, electrical energy storage systems, and are strongly dependent on insolation. The presented scenario can be totally changed if signiﬁcant inventions are made, such as, foe example, light, durable and cheap electrical energy batteries. The conclusion of the scenario discussions was further research under the project PATH-TO-RES should focus more on energy saving aspects than on construction of new power generation units.

4.5. Indicators – sum-up of energy roadmaps The tables below present basic indicators concerning energy roadmaps for Gdańsk. The indicators include: primary energy consumption, ﬁnal energy consumption, indicators and amounts of CO2 emission. PRIMARY ENERGY

2008

2012

2020

2050

Primary energy total [GWh]

9071

9426

9654

8547

Primary energy per resident [GWh/cap]

0.0200

0.0206

0.0211

0.0201

Hard coal

4661

4376

3030

1900

Natural gas

968

1051

2282

1830

Coke

Heating oil

145

116

Mazout

692

527

504

Diesel oil

1054

1159

1043

527

Petrol

870

1044

1149

174

LPG

308

400

Aircraft fuel

Municipal waste

Biogas+hythane

680

Biomass

300

580

819

1580

Liquid biofuels

192

500

Liquid synthetic fuels (from CO2)

500

Hydrogen

500

Solar energy

200

Geothermal energy

ENERGY CONSUMPTION

2008

2012

2020

2050

Energy consumption total [GWh]

6645

7097

7431

6916

Energy consumption per resident [GWh/cap]

0.0147

0.0155

0.0163

Industry (with the exclusion of LOTOSu) [GWh]

611

477

487

420

Public sector and services [GWh]

596

655

658

660

Private sector [GWh]

3168

3232

3323

3051

Transport [GWh]

2270

2734

2962

2785

Jerzy Buriak / Gdańsk University of Technology Marcin Jaskólski / Gdańsk University of Technology

CO2 emission [thousand tons]

2008

2012

2020

2050

Hard coal

1510 194 11 40 181 278 215 69 3 0 0 0 0 0 0 0 0 448

1418 211 9 32 138 306 258 90 3 0 0 0 0 1 0 0 0 234

982 458 6 16 132 275 284 90 5 0 0 0 0 5 0 0 0 8

616 368 4 1 0 139 43 14 5 0 0 0 0 37 0 0 0

Natural gas Coke Heating oil Mazout Diesel oil Petrol LPG Aircraft fuel Municipal waste Biogas+hythane Biomass Liquid biofuels Liquid synthetic fuels (from CO2)

Hydrogen Solar energy Geothermal energy Import of electrical energy

181

CO2 emission

2008

2012

2020

2050

Total CO2 emissions* [thousand tons]

2949

2699

2260

1407

CO2 emissions per resident [thousand tons /cap] 0.0065 0.0059 0.0050 0.0033

2. SUM-UP The key entities, energy companies in particular, operate independently of one another, whereas it is necessary to coordinate the plans of companies and the plans of local authorities. There is no regional energy agency. Such an agency would be responsible for supervision and coordination of long-term energy planning in the region, which now is the competence of the Marshall’s Ofﬁce. It should also be remembered that municipalities, including the municipality of Gdańsk, develop their own plans and assumptions to energy supply plans. That is why it obvious that such plans should be coordinated by a competent body. Moreover, the activities initiated in the region or the municipality by a competent energy agency could result in actual implementation of the plan. Now the strategies are not accompanied by action plans and that is why their assumptions turn out to be unfeasible. The planning process should be an iterative process, in which there is a sort of feedback loop, consisting in improving the strategy based on the experience from implementation of strategic objectives, included in the previous version of the strategy. Most often, however, an energy plan is put ad acta, and its new version is not planned, while it should be developed every 5 years.

Energy Roadmaps for the City of Gdańsk

LITERATURE 1. Regional energy strategy, with special emphasis on renewable sources in Pomeranian Region for the period of 2007–2025, commissioned by Pomeranian Region Executive Board, based on the resolution No 250/04 of Pomeranian Region Parliament of 01.03.2004, August 2006. 2. Energy policy and the role of bioenergy in Poland, BioENPol Project implemented by Gdańsk University of Technology, Euroepan Entre of Renewable Energy EC BREC University in Lund. 3. EC Wybrzeże, Annual Report 2007, http://www.ecwybrzeze.pl/pdf/EC_raport_2007.pdf. 4. Development strategy for Gdańsk till 2015, Operational programmes implementing the strategy in the period of 2005–2009. 5. Statistical yearbooks of Pomeranian Region 2005, 2006, 2007, 2008, Statistical Ofﬁce in Gdańsk. 6. Draft assumptions to the plan of heat, electrical energy and gas fuels supply in Gdańsk, Energoprojekt Katowice S.A., 2005. 7. Renewable Energy Roadmap – Renewable energies in the 21st century, European Commission (EC 10.01.2007). 8. National Energy Efﬁciency Action Plan (EEAP) 2007, Ministry of Economy, Warszawa, June 2007. 9. Jaskólski M., Modelowanie rozwoju regionalnych systemów energetycznych ze szczególnym uwzględnieniem bioenergii, doctoral dissertation, Gdańsk University of Technology, Gdańsk 2006. 10. Przanowski K., Praca systemów elektroenergetycznych – Part I, Politechnika Łódzka, Łódź 1983. 11. Google maps http://maps/google.com/

Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

Authors / Biographies

Jan Kiciński Gdańsk / Poland

Piotr Lampart Gdańsk / Poland

Deputy director for scientific research and head of the Department of Rotor Dynamics and Slide Bearings in the Institute of Fluid-Flow Machinery of Polish Academy of Sciences in Gdańsk, researcher, expert of Polish and international organizations, academic teacher. He graduated from the Faculty of Mechanical Engineering of Gdańsk University of Technology (1972). He successfully presented his PhD thesis in the Institute of Fluid-Flow Machinery of Polish Academy of Sciences (1979), and his habilitation thesis in AGH University of Science and Technology in Cracow (1986). He was awarded the title of professor of technical sciences in 1995. He managed three EU supported projects, which resulted in industrial implementations related to modern technical diagnosis systems in power engineering. He also managed a big commissioned project (PBZ 038–06), which was to develop the first Polish vibration control system of high voltage generation sets. In 2004 he was appointed the director of national Centre of Advanced Technologies RIMAMI, involving a few universities and selected power distribution and supply companies. Two years later he became a coordinator of national Scientific Network EKO-ENERGIA. In 2007 he became the Chairman of the Programme Council of the Baltic Eco-Energy Cluster, the biggest cluster in the sector in Poland, participated by over 50 economic, local self-governmental and scientific entities.

Dr Lampart graduated from the Faculty of Applied Physics at the Gdańsk University of Technology in 1986. In 1995, he was granted a PhD title in technical science in mechanics, specialising in fluid mechanics in The Szewalski Institute of Fluid-Flow Machinery PAN. In 2008 he was granted the title of doktor habilitowany nauk technicznych [senior doctorate in technical science] in machine construction and operations, specialising in rotary thermal machines. Since 1987, he works in The Szewalski Institute of Fluid-Flow Machinery PAN, presently holding the position of docent in Zakład Aerodynamiki Turbin [Institute for Turbine Aerodynamic]. His main interest focuses on calculation methods in fluid mechanics, optimisation of turbine flow system efficiency, turbine aerodynamics, cogenerations of heat and power, renewable energy sources. He is the author and co-author of over 90 publications in Polish and international scientific journals and conference papers. He has been a speaker at over 50 conferences in the country and abroad. Dr Lampart is also a co-author of over 40 studies and analysis for the industry sector.

Cogeneration in a Large and Small Scale

COGENERATION IN A LARGE AND SMALL SCALE Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

INTRODUCTION Cogeneration is a simultaneous production of electric energy and heat which leads to a more efficient utilisation of primary energy. Thus, cogeneration brings considerable savings in the final energy production and contributes to decrease the level of emissions into the environment, especially CO2. The opportunities for cogeneration are however usually determined by the demand on heat, which can very for example seasonally and with the daytime. The complex analysis of a cogeneration unit should take into account the characteristics of the heat receiver. Sample quantitative gains from cogeneration are displayed in Fig. 1. As seen from the picture, in order to produce 21 units of electric energy and 33 units of heat in cogeneration (assuming the theoretical total cogeneration efficiency of 90%) there are 60 units of primary energy required, whereas 97 units of primary energy are needed to produce the same amount of final energies in separate generation. SEPARATE GENERATION (efficiency 55%) loss 39 electric energy efficiency 35%

heat efﬁciency 35% loss 4

COGENERATION (efﬁciency 90%) electric energy

heat

loss 6

Fig. 1. Production of electric energy and heat in a separate mode and in cogeneration

Cogeneration in a large scale Prime movers in large CHP systems are ﬁrst and foremost steam turbines – backpressure or extractioncondensing steam turbines operating in a closed Rankine cycle as well as gas turbines operating in a Bryton cycle [1]. Combined two-fuel steam-gas cycles are also encountered. In a closed cycle of a back-pressure turbine (Fig. 2), the production and superheating of steam takes place in a boiler. The superheated vapour expands in a turbine and, from the turbine outlet, is directed to the heat exchanger (condenser) where it gives away its remaining superheat and condensation heat for heating of district net water. One asset of the back-pressure Abstract Main energy conversion machinery used and to be used in cogeneration systems are schematically described. First, large-scale cogeneration systems used in large power industry are discussed. Then, some assets of distributed generation are pointed out and small-scale cogeneration systems designed for energy units of distributed cogeneration are described.

Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

turbine system is its simplicity, another is low demand for cooling water and therefore low heat losses in the condenser. Among a number of disadvantages are a short expansion line (with the region of low pressures and temperatures exempted from the electric energy production) and a large stiffness of the system, that is the dependence of the electric energy production on the demand on heat. TURBINE

BOILER

GENERATOR ELECTRICITY

FUEL

HOT WATER

Fig. 2. A cogeneration cycle with a back-pressure turbine

In the extraction-condensing turbine (Fig. 3) the steam extraction point is located one, two or more turbine stages upstream of the outlet diffuser. An advantage of this design is the possibility of expansion down to the parameters below 0.1 bar and 40oC, which is important for the purpose of production of electric energy. Extraction-condensing turbines are met to operate in a power range from a few to a few hundreds of MWe. Truly, the exhaust heat is lost in the condenser in extraction-condensing turbines, but the heat load of the extraction points can, with application of some special designs, change in a wide range with practically little loss to the electric energy production. One way to adapt blading systems of extraction-condensing turbines to variable load operation in the context of cogeneration of electric energy and heat is the adaptive control. The main element of adaptive control is the so-called adaptive stage of flexible geometry located directly downstream of the extraction point. Basically, during extraction of steam to the extraction point this flexible geometry enables reduction of the mass flow rate in the blading system without a reduction of pressure drop in downstream stages. Thus, the full available pressure drop is used in the blading system. Expansions beyond the blading system, involving a loss of turbine power and giving rise to uncertainty in operation of the exit diffuser, are avoided. TURBINE

BOILER

GENERATOR ELECTRICITY

FUEL

STEAM

HOT WATER

COOLING WATER

Fig. 3. A heat cycle of the extraction-condensing turbine

In the most typical design the adaptive stage has throttling nozzles that have movable leading edges blocking part of the blade-to-blade passage if necessary, Fig. 4 – part A. This construction has been used by LMZ, ABB-Zamech, Alstom Power [2], [3]. Fig. 4 – part B illustrates another design of the adaptive stage nozzles with the same driving mechanism, but with a more complex division line of the stator blade. An interesting design of adaptive stator blade was patented in [4]. The adaptive stage stator has a rotated trailing edge (ﬂap nozzle)

Cogeneration in a Large and Small Scale

which controls the throat. As compared to the design with movable leading edges, this design maintains the smoothness of the proﬁle shape, also for low levels of throat opening, Fig. 4 – part C. A similar principle lies behind the system with rotated stator blades, Fig. 4 – part D.

Fig. 4. Adaptive stage nozzles: blade with a movable leading edge (A), blade with a complex division line (B), blade with a rotated trailing edge – ﬂap (C), rotated blade (D); 1 – full opening, 2 – part-load opening

LP inlet

extraction point LP exit

SAGE GROUP POWER [MW]

The numerical analysis of effects of adaptive control in a group of stages of a large power LP turbine (as in Fig. 5) based on the rotated blade design is presented in [5]. Fig. 6 exhibits changes of power in a group of two exit stages (last and last-but-one stage) as a function of mass flow rate during extraction of steam to the extraction point. Changes of power are plotted for different stator blade stagger angles (coloured solid lines) and for different pressure drops through the stage group (coloured dashed lines). Several point are marked to help to estimate the advantages of adaptive control. They are: N – nominal operation point; A – sample operation point under conditions of extraction of additional 10% of the turbine mass flow rate to the extraction point, and A’ – the same point of operation after adaptive control. The aim of adaptive control is to take advantage of the full pressure drop available and to bring the expansion back to the turbine blading system. It follows from Fig. 6, this can be achieved by closing last-but-one stator throats and rotating the blades by 2o. Point A is then moved to point A’ that lies on the line of nominal pressure drop in the stage group from 0.39 to 0.10 bar. A significant reduction of flow losses especially in the last stage can be achieved as a result of that. It was calculated that for a considered extraction-condensing turbine of power 50 MW, under conditions of a 10% mass flow rate extraction to the extraction point located upstream of a group of two exit stages, power gains reach on average 2.5 MW per stage. The stage group power is then lower by about 11% than the power before the steam extraction (6,5 MW), and is practically decreased by the decreased mass flow rate through the blading system. Note that for a 50MW turbine the power increase obtained from the adaptive control amounts to about 10% of the turbine power.

MASS FLOW RATE

Fig. 5. Geometry of the ﬂow system of the LP extraction-condensing turbine in meridional view

Fig. 6. Changes of stage group power as a function of mass ﬂow rate

In large cogeneration systems also gas turbines are often used. A sample cogeneration cycle with a gas turbine operating in an open cycle is illustrated in Fig. 7. Compressed air is fed to the combustion chamber where

Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

the fuel is burned under constant pressure. Heat is passed to the flue gases which expand in the turbine driving a generator. The exhaust gases from the turbine of temperature still in the region of 400-600oC first go to the recuperator, then to the heat exchanger where the district net water is heated. Due to a relatively high temperature of exhaust gases, combined gas-steam heat cycles with cogeneration can also be build. The efficiency of production of electric energy can exceed 50% there. Among advantages of gas turbines as prime movers in cogeneration systems are large efficiency of energy production and a relatively quick start-up to the nominal operation. The electric power of gas turbines usually does not exceed 100 MWe. exhaust gases hot water recuperator Heat exchanger Fuel Compressor

Combustion chamber

Air

Turbine

electric grid

Generator

Fig. 7. A cogeneration cycle with a gas turbine

Distributed generation Cogeneration as a simultaneous production of electric energy and heat can especially be applied in small power units of distributed generation systems [6], [7]. The development of these small power units is not centrally planned. Classification of distributed generation units refers mainly to electric power units with the possibility of heat generation. Probably the most adequate division of distributed generation units according to the generated power is as follows: • micro distributed generation (up to 5 kW) • small distributed generation (5 kW – 5 MW) • medium distributed generation (5 MW – 50 MW) • large distributed generation (50 MW – 100 or 150 MW). There are many different technologies of generation of electric energy and heat in distributed sources. Distributed generation units can be small conventional power plants, small coal-based heat or heat and power stations, biomass heat stations, hydro power plants, wind farms, off-shore wind farms, solar stations, fuel cells and energy storage systems, biogas and biorafinery stations, Fig. 8. In the latter, a simultaneous production of fuels, electric energy and heat can take place. Although the upper power limit for the distributed generation units has been set about 100-150 MW, we will further refer to small and micro distributed generation systems of power not exceeding 5 MWe. In small and micro distributed generation systems, the produced energy goes first to local communities. One can mention here the energy generation for households, residence buildings, large farms, public buildings or small and medium enterprises. The surplus of electric energy goes to the power network, heat surplus goes to local district heating networks, whereas the surplus of fuel can be used for transportation or compressed into a gas network.

Cogeneration in a Large and Small Scale

microgrid

low emission conventional power station

wind farm

Water power plant

hydro power station solar station

off-shore wind farm heat station

Micro CHP micro CHP

solar

sea wave energy

production of energy plants

Micro CHP fuel cells

store H2

energy store

Fig. 8. Model of distributed generation

There are several advantages of distributed generation such as: • possibility of utilisation of local energy resources, especially renewable energy sources • production of different forms of final energy in cogeneration • avoiding excessive installed power in a single location • reduction of peak load • reduction of transmission losses • increasing energy safety by diversification of energy sources • reduction of green-house gas emissions (cogeneration, renewable energy sources). Among disadvantages of distributed generation one can mention: • uncertainty of energy production from some sources (wind farms, solar units) and the necessity to keep power reserves • high initial investment costs • high costs of energy measurement and billing per unit of produced power. The policy of European Union is favourable for distributed generation and renewable energy sources, only to mention: • directive 2004/8/EU in point of cogeneration • directive 2003/87/EU in point of trading limits in green-house gases emission • directive 2003/96/EU in point of taxation of energy products and electric energy • directive 2001/77/EU concerning the share of renewable energy in the energy balance of membering countries. The profitability of energy production in distributed generation units can be increased due to a programme of economic incentives such as green certificates for energy from renewable resources, red certificates for cogeneration, certificates for energy efficiency or low charges for entry to network connections. There are also a number of regulations that can act either in favour or against distributed generation, for example: • regulations concerning entry of distributed generation units to network connections

Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

• environmental regulations concerning emissions of green-house gases and other harmful emissions (SO2, NOx), dust pollutions, noise emissions, landscape deterioration or other bad impact on the environment • regulations concerning security and safe operation.

Cogeneration in a small scale Primary movers for cogeneration units operating within the distributed generation systems are ignition (spark and diesel) engines. Power units based on ignition engine cycles topped with a recovery heat node are main components of cogeneration systems integrated with the production of fuels from biomass in biogas and biorafinery stations. Equipped with appropriate feeding and ignition systems can burn both gas and liquid fuels, also less caloric fuels such as biogas from fermentation biogas stations, gas obtained from pyrolytic gasification, liquid products of fermentation and pyrolysis or products of estrification of animal fat. A basic power range for ignition engines is from a dozen kWe to a few MWe. A cogeneration cycle for ignition engines is illustrated in Fig. 9. The piston ignition engine drives a generator of electric energy. Heat from the cooling and lubrication cycle can be used for heating net water. Heat recovered from exhaust gases can be used for the production of technological steam and also for district heating. exhaust gases STEAM

fuel air GENERATOR ELECTRICITY

DIESEL ENGINE

HOT WATER lubricant Cooling liquid

Fig. 9. A cogeneration cycle for the piston ignition engine

Main advantages of small power stations based on piston ignition engines are: • high efficiency of electric energy production, also during low load operation • possibility of quick start-up to the nominal operation conditions • possibility of operation in places distant from entry to the distribution network and as an emergency supply • variable fuel supply • relatively low investment costs. In small or micro distributed cogeneration systems gas turbines or microturbines can also be applied. The idea of cogeneration cycle is the same as for large power objects (Fig. 7). Gas turbines are characterised by a significantly longer exploitation time as compared to piston engines and require less frequent maintenance services. The efficiency of electric energy production however is usually by a few per cent lower than that of the ignition piston engines in the considered range of power. Initial investment costs are also higher. The counterparts of large power turbines in distributed generation are small steam turbines or microturbines that operate in an organic Rankine cycle (ORC) whose schematic is presented in Fig. 10. Main components of this CHP station are ecological boiler fit to combust different kinds of biomass or biofuels, intermediate heat cycle to extract heat from flue gases to thermal oil as a heat carrier, evaporator, turbine with a low boiling liquid as a working medium, generator, condenser and circulating pumps for the working medium and thermal oil [8], [9]. In the presented heat cycle, electric energy is a by-product and forms only about 10-20% of the total

Cogeneration in a Large and Small Scale

heat. The remaining superheat and condensation heat of the working medium is used for heating net water. The solution offers a possibility to apply low temperature heat sources, allows utilisation of different types of fuels and modular construction, which facilitates adaptation of the CHP unit to the required power range. Micro CHP units dedicated for individual households of total heat capacity up to 20kWt and electric power up to 4kWe as well as small CHP modules dedicated for communal energy centres of total heat capacity 1000kWt and electric power 200kWe (maximum up to 5 MWt and 1 MWe respectively) are currently being elaborated at IMP PAN. In the power range of a few or a dozen kWe one can also consider cogeneration units with a Stirling engine (with external combustion) or based on a fuel cells system. ORC

wood, pellets electricity biogas hot water

thermal oil

low-boiling medium

Fig. 10. Cogeneration unit with ORC; E – evaporator, TV – steam turbine, C – condenser, G – generator vapour microturbine ORC

Heat consumers

INTEGRATED BIORAFINERY

Hot water

Biomethane

Electricity Diesel engine

Electric energy consumers

vapour microturbine (OCR)

Hot water

biogas station

heat consumers

Biomethane air

fuel Electricity Electric energy consumers Gas microturbine

Fig. 11. Schemes of cogeneration units in a combined cycle: A – diesel engine + ORC cycle; B – gas turbine + ORC cycle; TV – steam turbine, TG – gas turbine, G1, G2 – generators, C – compressor, BC – gas turbine combustion chamber, HE – heat exchangers

Jan Kiciński, Institute of Fluid Flow Machinery, Polish Academy of Sciences Piotr Lampart, Institute of Fluid Flow Machinery, Polish Academy of Sciences

Aiming at the development of cogeneration technologies integrated with systems of production of fuels from biomass which are characterised by a high efﬁciency of electric energy production (40-50%), works on combined steam/gas cycles illustrated schematically in Fig. 11 are in progress at IMP PAN. It seems that cogeneration units of electric power 0.5-1MWe will most often be used. The main heat cycle is that of the ignition engine or gas turbine, where the generator is driven by the ignition engine or gas turbine. An additional heat cycle in a steam ORC cycle working based on heat recovered from engine/gas turbine exhaust gases or cooling systems. The steam turbine drives another generator which produces additional amount of electric power. The remaining superheat and condensation heat of the working medium in the ORC cycle is then used for heating net water.

Summary Main CHP technologies used in large power industry and distributed generation were presented. As for large CHP units particular attention was paid to extraction-condensing turbines. Advantages of adaptive control, which allows changes of heat load of extraction points with little detriment to the production of electric energy, were illustrated. The assets of distributed generation and a number of CHP technologies suitable for distributed generation units were also discussed. The paper was focused on CHP stations equipped with ORC modules. It seems that in the years to come many machines of this type will be applied in distributed generation units based on biomass. They are: • micro CHP stations of heat capacity up to a few dozens kWc and electric power up to a few or a dozen kWe dedicated for individual households (Household CHP stations) • small CHP stations of heat capacity up to 5 MWc and electric power up to 1 MWe dedicated for local communities (Communal Energy Centres) • small CHP stations in a combined steam/gas cycle integrated with systems of production of fuels from biomass and characterised by a high efﬁciency of electric energy production within a power range of 0.5-1MWe.

LITERATURE 1. Perycz S., 1992, Steam and gas turbines, Edition of Polish Academy of Sciences, Fluid Flow Machinery Series, Vol. 10, Wrocław–Warszawa–Kraków, Ossolinuem Press, Poland (in Polish). 2. Budyka I., Bułanin W., Kantos S., Rodin K., 1959, Collection of steam and gas turbine designs, Gazenergoizdat, Moscov (in Russian). 3. Dejcz M.E., Filippov G.A., Lazarev L.Ja., 1965, Collection of axial turbine cascade profiles, Maszinostrojenie, Moscov (in Russian). 4. Puzyrewski R., 1978, Stator cascade for mass flow control in a heat turbine, Patent Office, Poland, No 96981, 1978– 07–05. 5. Lampart P., Puzyrewski R., 2006, On the importance of adaptive control in extraction/ condensing turbines, ASME Pap. GT2006-91160. 6. Distributed Energy Peer Review, December 2005, Darlington, USA. 7. Polimeros G., 2002, Energy Cogeneration Handbook, Industrial Press Inc. 8. http://www.turboden.it/en/ 9. Mikielewicz J., Bykuć S., Mikielewicz D., 2006, Application of renewable energy sources to drive ORC mikro CHP, In: Heat transfer and Renewable Sources of Energy, Eds: Mikielewicz J., Nowak W., Stachel A.A.

rg nergetica.o e a t c .a w w w

Roman Korab / Silesian University of Technology

Authors / Biographies

Roman Korab Gliwice / Poland Roman Korab (born in 1973) graduated from Electrical Engineering Department of Silesian University of Technology. He was awarded the degree of doctor of technical sciences for his thesis entitled “Models of Efﬁcient Transmission Tariffs in Electrical Power Grids” (2003). Since 1998 he has been connected with the Institute of Electrical Engineering and Control of Silesian University of Technology. His research interests focus mainly on transmission operation in electrical power market. He is an author or a co-author of over 50 publications. He is a member of IEEE.

Locational Marginal Prices (and Rates) – Harmonization of Market Solutions with New Development Trends

LOCATIONAL MARGINAL PRICES (AND RATES) – HARMONIZATION OF MARKET SOLUTIONS WITH NEW DEVELOPMENT TRENDS Roman Korab / Silesian University of Technology

INTRODUCTION The current architecture of Polish electrical energy market is based on the concept of “copper plate”, according to which energy trading is made without taking into consideration laws of electrical engineering, which govern power flow in electrical energy grid, and neglects technical constraints connected with energy supply from producer to consumer. In “copper plate” model, however, settlement price is the same for all market participants (the same for all locations in the system), and its value at a given hour depends exclusively on the price offered by the final producer that completes the generation process. The price does not take into consideration the costs connected with transmission losses and grid constraints. The costs are transferred to market participants (usually only to consumers) through transmission charge and most often they are averaged within a given group of consumers (the so called “postage stamp method” is used). Theoretical analysis and practical experience of other countries indicate that there is a more adequate model in the electrical energy market, inter alia from the point of view of widely understood security of supply, namely the model based on Locational Marginal Prices (LMP). Locational marginal prices differ, depending on location of the given participant of the market in the electric energy system, and include the component connected with cost of energy purchase to balance the demand, the component connected with transmission losses and the component connected with grid constraints. In the model based on the concept of locational marginal prices, on making trade transaction, market participants take into consideration laws of electrical engineering that govern power flow and technical constraints connected with energy supply from producer to consumer. As a result of that, current (operational) security of the system functioning is higher than in the “copper plate” model [1]. Additionally, short-term locational marginal prices (and the resultant locational marginal rates of transmission charge that transfer costs of losses and grid constraints) generate relevant economic incentives that can affect both the decisions on location of new power plants, and the direction of (technological) development of the system, that is the decisions whose consequences are seen in the long time perspective. The further part of the article is devoted to these aspects.

SHORT-TERM LOCATIONAL MARGINAL PRICE – DEFINITION AND PHYSICAL INTERPRETATION According to the definition proposed by the authors of the theory of locational marginal prices [2, 3], locational marginal price equals minimum change of balancing demand in electrical power system, caused by change of the power received in the given grid node, which can be expressed by the following formula: Abstract The model of electrical power market functioning in Poland is based on the concept of “copper plate”, whose main assumption in that energy trading can be made with no reference to laws of electrical engineering, which govern power flow in electrical energy grid, and which neglects technical constraints connected with energy supply from producer to consumer. Such a solution means ineffective operation of the market, both current and investment market. An alternative solution, eliminating the deficiency of “copper plate” model is provided by a market mechanism based on the concept of short-term locational marginal prices, which are an element integrating the laws of electrical engineering and economics. Differentiating

prices depending on the location of individual producers and consumers in the system is the essence of the solution, thanks to which the participants of the market receive economic signals on, inter alia, desired locations of new generation capacity, estimated level of the power, required for local balancing of demand. The article presents the results of the simulations made on models of national power grid, illustrating properties of the model of locational marginal prices. The results of the analyses that take into consideration development of nuclear power generation and distributed power generation were also presented.

Roman Korab / Silesian University of Technology

(1) where PLi denotes active load received in node i, and K(PGi) is cost of balancing demand, equal to the sum of the products of the volume of the power used to balance demand and the related offer prices of producers. It follows from the above definition that locational marginal price reflects cost of supply of additional energy unit to the given grid node. A simplified way of determining it, enabling an easy physical interpretation of locational marginal price, can be traced on the following example. In the system shown in Fig. 1, there operate three producers offering energy at various prices cGi. The producers are connected with one another and with consumers via a closed grid. The system operator balances demand, distributing loads among producers as needed, taking into consideration transmission losses and grid constraints. Generation by individual producers PGi is determined in such a way as obtain minimum cost of demand balancing. For the state of the electrical power system presented in Fig. 1a, the cost equals K1. c G1 PG1

c G3

c G2 PG2

PG3

PL2

PG1 +�PG1

c G2 PG2 +�PG2

c G3 PG3 +�PG3

K2 = cG1(PG1 +�PG1) + cG2(PG2 +�PG2) + cG3(PG3 +�PG3)

K1 = cG1PG1 + cG2PG2 + cG3PG3

PL1

c G1

PL3

PL1 +�PL1

LMP1 = (K2 - K1)/�PL 1

PL2

PL3

Fig. 1. Simpliﬁed way of determining locational marginal price: a) base state, b) state after demand increase in node L1

To determine the value of locational marginal price LMP in node L1, demand PL1 should be increased by a certain small value ∆PL1. The increased demand makes it necessary to change generation distribution by ∆PGi, and consequently, to change balancing cost. For the state of the system after demand increase, the cost is K2 (Fig. 1b). The difference of demand balancing costs for both states of the system (before and after demand increase in node L1), divided by demand increase in that node (i.e. by ∆PL1), equals locational marginal price LMP in node L1, but if ∆PL1 = 1 MW, then the difference of costs K2 and K1 directly equals locational marginal price LMP1. We can determine the values of LMP in the other nodes in the same way. By decomposing locational marginal price, it can be proved [4÷7] that it includes many components of simple physical interpretation, such as: • locational marginal cost of electrical energy in reference node • cost of grid losses • cost of branch constraints (connected with permitted load-carrying capacity of the line and transformers) • cost of voltage constraints (connected with permitted voltage levels). The analytical form of the components is as follows: (2) where LMPb denotes locational marginal price in reference node, Pstr – losses of active load in the grid, Sij – ﬂow of apparent power in the branch connecting nodes i and j, Uj – voltage magnitude in node j, µ – Lagrange multiplier connected with relevant inequality constraint, and n is the number of nodes in the analyzed grid. Short-term locational marginal prices should be determined during the optimal work status of the electrical energy system, which is, generally speaking, understood as a state in which costs of demand balancing reach the minimum value on meeting the technical constraints connected with energy generation and supply to consumers. The problem of Optimal Power Flow (OPF) is applied to determining values of locational marginal prices [8].

Locational Marginal Prices (and Rates) – Harmonization of Market Solutions with New Development Trends

LOCATIONAL MARGINAL PRICES IN NATIONAL POWER GRID (NPG) Annual values of locational marginal prices in normal work status of Polish electrical energy system1 were determined by the use of the OPF and the models of the national grid 400/220/110 kV, reflecting the winter and summer peak and off-peak. The obtained results are illustrated in Fig. 2, in which the average value of LMP in the given area of National Power Grid (column) and the minimum and maximum values of those prices are marked. Fig. 2. Annual weighted means of locational marginal prices LMP (PLN/MWh) in individual areas and voltage levels of National Power Grid 400/220/110 kV An analysis of the obtained results indicates that in the entire National Power Grid 400/220/110 kV maximum value of locational marginal price is 162.54 PLN/MWh, and minimum value - 130.70 PLN/MWh (it is 139.54 PLN/MWh on average in National Power Grid). The highest values of locational marginal prices (regardless of voltage level) occur in the area of operation of ODM Bydgoszcz, and the lowest in ODM Katowice. There is also a considerable changeability of locational marginal prices in the nodes located inside individual areas. The LMP differences in the given area are mainly due power balance and grid density in that part of the system. It is reflected in the results obtained in ODM Katowice (balance of generation and consumption and big density of the grid result in small differences of LMP at all voltage levels), and in the areas of ODM Bydgoszcz and ODM Warszawa (bigger differences of locational marginal prices is the result of negative power balance in the area – bigger consumption than production – and relatively poor development of the grid in that part of the country). The growing differences of locational marginal prices can thus be a symptom of deteriorating level of security of supply in the given part of the system. The analyses indicate that in normal work conditions of National Power Grid, differences of locational marginal prices in individual grid nodes 400/220/110 kV are at a moderate level, reflecting the adopted level of differences of prices offered by producers. However, in National Power Grid there can occur situations in which the differences in LMP between individual areas (and even grid nodes) are very big. Such a situation, hypothetical for the time being, is illustrated in Fig. 3, which presents the results obtained for the National Power Grid model in which the planned merger with the Lithuanian system (energy export from National Power Grid of 1500 MW was modelled) was taken into consideration. The system assumes extension of national transmission grid (new 400 kV lines were marked with a dashed line), but despite its extension, with the export of 1500 MW to the Lithuanian system, it was not possible to meet all the grid constraints (mainly in 110 kV grid). That is why in the calculations for this example grid constraints were neglected, as a consequence of which the differences of locational marginal prices between individual result only from power losses. Fig. 2. Annual weighted means of locational marginal prices LMP (PLN/MWh) in individual areas and voltage levels of National Power Grid 400/220/110 kV

An analysis of the obtained results indicates that in the entire National Power Grid 400/220/110 kV maximum value of locational marginal price is 162.54 PLN/MWh, and minimum value – 130.70 PLN/MWh (it is 139.54 PLN/MWh on average in National Power Grid). The highest values of locational marginal prices (regardless of voltage level) occur in the area of operation of ODM Bydgoszcz, and the lowest in ODM Katowice. There is also a considerable changeability of locational marginal prices in the nodes located inside individual areas. The LMP differences in the given area are mainly due power balance and grid density in that part of the system. It is reﬂected in the results obtained in ODM Katowice (balance of generation and consumption and big density of the grid result in small differences of LMP at all voltage levels), and in the areas of ODM Bydgoszcz and ODM Warszawa (bigger differences of locational marginal prices is the result of negative power balance in the area – bigger consumption than production – and relatively poor development of the grid in that part of the country).

It was assumed in the calculations that the average price of the energy offered by centrally managed generation units equals 137.40 PLN/MWh (maximum price = 163.16 PLN/MWh, minimum price = 107.03 PLN/MWh).

Roman Korab / Silesian University of Technology

The growing differences of loca-tional marginal prices can thus be a symptom of deteriorating level of security of supply in the given part of the system. The analyses indicate that in normal work conditions of National Power Grid, differences of locational marginal prices in individual grid nodes 400/220/110 kV are at a moderate level, reďŹ&#x201A;ecting the adopted level of differences of prices offered by producers. However, in National Power Grid there can occur situations in which the differences in LMP between individual areas (and even grid nodes) are very big. Such a situation, hypothetical for the time being, is illustrated in Fig. 3, which presents the results obtained for the National Power Grid model in which the planned merger with the Lithuanian system (energy export from National Power Grid of 1500 MW was modelled) was taken into consideration. The system assumes extension of national transmission grid (new 400 kV lines were marked with a dashed line), but despite its extension, with the export of 1500 MW to the Lithuanian system, it was not possible to meet all the grid constraints (mainly in 110 kV grid). That is why in the calculations for this example grid constraints were neglected, as a consequence of which the differences of locational marginal prices between individual result only from power losses.

Fig. 3. Locational marginal prices LMP (PLN/MWh), in individual areas and voltage levels of 400/220/110 kV network of National Power Grid, with the export of 1500 MW to the Lithuanian system

The export of energy from National Power Grid to the Lithuanian system considerable increases the value of locational marginal prices in the north-eastern regions of the country as compared to the regions where there is no such export. It is due to the fact that the exported energy must be transmitted from distant sources, which results in very strong increase of power loss in 400/220/110 kV network of National Power Grid (the losses are 857 MW, with 617 MW for the same system in which there is no export). One of the possibilities of reducing power losses consist in construction of new lines, but it must be noted that at present that way is not very realistic (due to formal and legal difďŹ culties connected with construction of new lines, in particular in the

Locational Marginal Prices (and Rates) – Harmonization of Market Solutions with New Development Trends

in areas of natural assets). The other, more feasible possibility consists in construction of sources of distributed generation. The analysis assumed construction of six co-generation sources of electrical power of 10 MW (locations: Augustów, Ełk, Grajewo, Olecko, Suwałki, Szczytno) and one gas storage source of the power of 50 MW (location: near the Ostrołęka power plant). The values of locational marginal prices after introduction of sources of distributed generation are presented in Fig. 4.

Fig. 4. Locational marginal prices (PLN/MWh), in individual areas and voltage levels of 400/220/110 kV network of National Power Grid, with export to the Lithuanian system of 1500 MW (a system with sources of distributed generation)

The analyses show that introduction of sources of distributed generation resulted in considerable decrease of the value of locational marginal prices in the area of north-eastern Poland. It is mainly due to the fact that operation of those sources contributed to signiﬁcant (ca 5%) reduction of active power losses in 400/220/110 kV network of National Power Grid. The presented example clearly shows how locational marginal prices LMP point out to the location of new sources (or generally, to location of new investments in the electrical power system). High values of those prices in the given area mean deﬁcit of generation capacity in the region (bigger demand than consumption), that is deteriorating security of energy supplies to end users. In the case of “copper plate” model, prices are averaged in the entire territory of Poland, as an effect of which the information about potential threat to security of supply in certain parts of the country is lost.

LOCATIONAL MARGINAL RATES TRANSFERRING COST OF LOSSES AND GRID CONSTRAINTS Short-term locational marginal prices LMP can constitute a base for determining the rates of transmission charge, transferring the costs connected with power losses and grid constraints, the so called rates of market

Roman Korab / Silesian University of Technology

charge [1]. Point-to-point types of rates, used in bilateral contracts, with clearly defined production and reception nodes are the first type of market charge rates. The value of point-point market charge rates equals the difference of locational marginal price in reception node and the price in production node, between which the bilateral contract was concluded [3]. In energy purchase, on Power Exchanges or in power trading companies, it is not possible to indentify where the energy was produced, because of the properties of electrical energy as a commodity. So the energy bought in this way cannot be charged with market charge of point-to-point type. It is possible to solve the problem by the use of locational marginal rates determined with virtual node [6]. With the assumption that generally producers and consumers pay transmission charge in the same proportion (share fifty/fifty the costs of transmission), locational marginal rates for producers and consumers are set by the following: (3)

(4) where LMPśr denotes the price in virtual node, described by the following formula:

(5)

LOCATIONAL MARGINAL RATES IN NATIONAL POWER GRID Like locational marginal prices themselves, locational marginal rates of market charge, clearly indicate the desirable, due to improvement of work conditions of electrical energy grid, location of new production units (high locational marginal prices lead to low charge rates for producers). The best locations are the nodes where charge rates have negative values, which means that in the model of the market in which producers participate in covering transmission costs, a producer connected to such a node not only has to cover the part of the costs connected with energy transmission but also receives allowance from the operator. The allowance is due to the fact that power generation in the location with negative charge rate favourably affects functioning of the entire system, by reducing the costs connected with losses and grid constraints. Currently the northern part of Poland is the area of National Power Grid of the lowest locational marginal rates. Below please ﬁnd presented the values of locational marginal rates in selected generation nodes, in 400 and 220 kV networks of the national grid, for two variants of National Power Grid development: with the assumption of building a nuclear power plant and with the assumption of development of distributed generation, the same in terms of the power installed. The analyses made use of 400/220/110 kV model of national power grid that takes into consideration the planned development of 400 and 220 kV network (according to the plan from mid 2008). The development referred mainly to better power supply to Warsaw, Wrocław and Poznań agglomerations, enhancement of National Power Grid on the North – South cross section. The demand for active power was 29.3 GW. In the variant with a nuclear power plant, two most likely locations of that type of source, i.e. the villages of Żarnowiec and Klempicz [9] were considered. Fig. 5 and 6 present the values of locational marginal rates in selected generation nodes of the voltage of 400 and 220 kV, and in the variant without and with the nuclear power plant in Żarnowiec and Klempicz (two power levels of the plants were considered: 1600 and 3200 MW).

Locational Marginal Prices (and Rates) – Harmonization of Market Solutions with New Development Trends

Fig. 5. Locational marginal rates of market charge in selected generation nodes of the voltage of 400 and 220 kV, in the variant without and with the nuclear power plant in Żarnowiec

In the variant without a nuclear power plant, locational marginal rates of market charge for producers adopt negative values in two (from among the selected ones) nodes: Żarnowiec and Ostrołęka. It is a clear signal of a deficit of production capacity in those areas. In the other locations, the charge rates are positive, and they are the highest in the nodes to which Bełchatów, Turów and Silesian power plants are connected. Connecting a nuclear power plant of the power of 1600 MW to Żarnowiec node changes power flow in the grid, leading, inter alia, to reduction of losses, and reducing the impact and number of active grid constraints, which results in change of locational marginal prices and, as a consequence, of locational marginal rates of market charge. From the point of view of national system producers, the change of locational marginal rates resulting from connecting a nuclear power plants to Żarnowiec node is good because the rates of the charge on the energy they produce are reduced. And as for Żarnowiec node, one can say that connecting a power plant of the power of 1600 MW to it is not favourable from the point of view of the producers located there, as the rate of the charge to be paid by them increases significantly. It means that, due balancing of local demand, such power is too big. The observed effects deepen when the power of the nuclear power plant connected to Żarnowiec node is increased to the level of 3200 MW.

Roman Korab / Silesian University of Technology

Fig. 6. Locational marginal rates of market charge in selected generation nodes of the voltage of 400 and 220 kV, in the variant without and with Klempicz nuclear power plant

The presented results of the analyses made with the assumption of locating a nuclear power plant in Żarnowiec node indicate that development of generation capacity in northern Poland will favourably inﬂuence the work condition of the entire National Power Grid. And if the nuclear power plant is located in Klempicz, the effects will not be so unambiguous, as the location is close to a few existing system power plants. As a result of that, in some nodes there is an increase of locational marginal rates. It refers, e.g. to the nodes to which condensation Bełchatów, Pątnów and Dolna Odra Power plants and Żarnowiec hydro power plant are connected. High values of locational marginal rates in Klempicz node itself mean that there is excessive concentration of production capacity in that region. These aspects should be taken into consideration when National Power Grid is, possibly, making decision on location of a nuclear power plant. Development of distributed generation sources can be an alternative to construction of a nuclear power plant in that production sub-sector of National Power Grid. Many work conditions of National Power Grid were analysed to assess the effects that can be obtained as a result of introducing distributed sources. It referred to the statuses for which development distributed generation of the total power of 3200 MW (power matching one of the variants considered in the analysis of impact of a nuclear power plant) was assumed. The additional assumption was that half of the power will be installed in wind sources, and the remaining part – in distributed sources, using other production technologies, e.g., sources based on biogas combustion. In the analyses of distributed sources were randomly connected to the nodes of a closed network of National Power Grid – wind sources in the area of northern Poland, and the other sources of distributed generation – in the entire territory of the country. Also the power of those sources was selected randomly (the selected power of wind farms was from 20 to 40 MW, and the power of the other sources - from 1 to 5 MW). There were 50 drawings. Locational marginal prices and rates were determined for each work statte of National Power Grid. Fig. 7 shows the results of calculation of locational marginal rates (average values from 50 random work states of National Power Grid) in selected generation nodes of the voltage of 400 and 220 kV.

Locational Marginal Prices (and Rates) – Harmonization of Market Solutions with New Development Trends

The analyzed results indicate that development of distributed power production/sources in National Power Grid will lead to signiﬁcant reduction of locational marginal rates in generation nodes of 400 and 220 kV (with the exception of Ostrołęka power plant, in which increase of locational marginal rate is observed, but its value still remains negative). It is mainly due to transferring production close to consumption points, as a result of which transmission losses are reduced and grid constraints are mitigated. And comparing the values of locational marginal rates for work states of National Power Grid with the assumed development of distributed power production/sources (Fig. 7) with relevant work states with the modelled nuclear power plant (Fig. 5 and 6), it can be observed that for the location of nuclear power plant in Żarnowiec the results in most generation nodes are similar, with one difference, however, namely, that with development of distributed generation there is no negative effect in the form of increase of locational marginal rate in Żarnowiec node. And the location of nuclear power plant in Klempicz gives deﬁnitely worse results than it from development of distributed sources.

Fig. 7. Locational marginal rates of market charge in selected generation nodes of the voltage of 400 and 220 kV, in the system without and with sources of distributed generation of the total power of 3200 MW

SUM-UP With the power sector functioning in market conditions, it should be the market that should create relevant economic signals supporting investment policy. Such signals can include, e.g. energy price – higher in the area where there is deﬁcit of production capacity. Differentiating prices depending on the location of individual producers and consumers in the system is the essence of the market model based on the concept of locational marginal prices LMP.

Roman Korab / Silesian University of Technology

But it is not true about the currently functioning in Poland “copper plate” model, characterized by the same price of energy in each node of the system. Lack of locational differences of prices in “copper plate” model is yet another factor discouraging potential investors from investing in those areas of the country that are behind in terms of development of the infrastructure providing for security of electrical energy supplies, which can lead to growing differences between individual regions of Poland and growing risk of losing the security of supply in some areas of the country. Apart from unambiguous indication of the areas preferred for location of new production capacity, economic signals generated by the market mechanism based on the model of locational marginal prices can also help estimate its volume required in individual locations, due to balancing the demand there. The presented results of the analyses indicate that excessive concentration of production capacity in a single node leads to deteriorating the situation of the producers connected to it. If a bigger number of smaller sources is installed, then the negative effects does not occur. The model of locational marginal prices is thus consistent with the new development trends in electrical power sector, of which sources of distributed generation are the essence. The presented research results were obtained under Commissioned Research Project “Power Supply Security of Poland” (PBZ-MEiN-1/2/2006), implemented by a consortium of Gdańsk, Silesian, Warsaw and Wrocław Universities of Technology. Locational marginal pices were determined by using MATPOWER simulation package [10].

Literature 1. Popczyk J., Żmuda K., Kocot H., Korab R., Siwy E., Bezpieczeństwo elektroenergetyczne w społeczeństwie postprzemysłowym na przykładzie Polski, Wydawnictwo Politechniki Śląskiej, Gliwice 2009. 2. Caramanis M.A., Bohn R.E., Schweppe F.A., Optimal Spot Pricing: Practice and Theory. IEEE Trans. on Power Apparatus and Systems, vol. PAS-101, No 9, September 1982. 3. Schweppe F.Z., Caramanis M.Z., Tabors R.D., Bohn R.E., Spot Pricing of Electricity, Kluwer Academic Publishers, Boston/Dordrecht/London, 1988. 4. Rivier M., Perez-Arriaga I., Computation and decomposition of spot prices for transmission pricing. 11th PSC Conference, Avignon, France, August 1993. 5. Xie K., Song Y.H., Stonhan J., Yu E., Liu G., Decomposition model and interior point methods for optimal spot pricing of electricity in deregulation environments. IEEE Transactions on Power Systems, vol. 15, No 1, February 2000. 6. Kocot H., Planowanie rozwoju sieci przesyłowej i 110 kV w warunkach rynku energii elektrycznej, PhD thesis, Gliwice 2000. 7. Korab R., Modele efektywnych taryf przesyłowych w sieciach elektroenergetycznych, PhD thesis, Gliwice 2003. 8. Wood A.J., Wollenberg B.F., Power Generation, Operation and Control, J. Wiley & Sons Inc., New York 1996. 9. Kasprzyk S., Program polskiej energetyki jądrowej – najkorzystniejsze lokalizacje, moce w tych lokalizacjach, rozwój i modernizacja sieci NN i rozdzielni NN, Przegląd Elektrotechniczny, No 9, 2009. 10. Zimmerman R.D., Murillo-Sanchez C.E., Thomas R.J., Matpower’s extensible optimal power ﬂow architecture, Power and EnergySociety General Meeting, 2009, IEEE, July 2009.

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

Authors / Biographies

Aleksander Kot Kraków / Poland

Jerzy Kulczycki Kraków / Poland

Graduated from the Faculty of Electrical Engineering, Automatics, IT and Electronics with the diploma of MSc. Engineer. (1997). He was awarded the degree of doctor in the same faculty (2005). Now he is employed as an assistant professor in the Chair of Electrical Engineering and Electrical Power of AGH University of Science and Technology. His professional interests focus on: analysis and estimation of distributionnetworks, optimization, artiﬁcial intelligence, forecasting and planning of network development, IT systems in the electrical power industry and energy markets.

Graduate of Silesian University of Technology in Gliwice (1956). He was awarded PhD in AGH University of Science and Technology in Kraków (1967), then, in 1976 – second level doctorate (habilitation) and became a professor in 1991. During the period of 1956–72 he was involved mainly in assembly and design of electrical power systems. Since 1972 – an academic teacher in AGH University of Science and Technology. His professional interests include electrical power engineering, in particular, methods of designing optimum system structures, enhanced efﬁciency of using property of electrical power systems.

Waldemar L. Szpyra Kraków / Poland He obtained the diploma of engineer electrician in the Faculty of Electrical Engineering of AGH University of Science and Technology in Kraków in 1975, and PhD – in the Faculty of Electrical Engineering, Automatics, IT and Electronics of AGH University of Science and Technology in Kraków in 1998. Now - an assistant professor in the Chair of Electrical Engineering and Electrical Power Engineering of his University. He is involved in modelling, work status estimation and optimization of distribution networks, application of artiﬁcial intelligence methods in electrical power engineering and electrical power management.

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

POSSIBILITIES OF LOSSES REDUCTION IN MEDIUM VOLTAGE DISTRIBUTION NETWORKS BY OPTIMAL NETWORK CONFIGURATION Aleksander Kot / AGH University of Science and Technology in Kraków Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar Szpyra / AGH University of Science and Technology in Kraków

1. COMPLEXITY OF NETWORK AND CONSUMER STRUCTURE Electrical power distribution networks play a very important role in electrical power system – they distribute energy and supply it to end users. Due to their function, they are characterized by extreme complexity, and they cover, practically speaking, the area of the whole country. These networks include 110 kV networks, enabling delivery of energy from UHV/110 kV stations and its initial distribution, and MV networks and LV networks, which are mainly responsible for distribution of energy to a great number of consumers. Table 1 presents, based on [1], the length of distribution network, by individual voltage levels. Apart from the ﬁgures given, LV connections of the total length of ca 145 000 km, not included in LV network here, should also be taken into consideration. Tab. 1. Length of electrical power lines according to the data for 2007 [1] Voltage level

Length [km]

110 kV network

32 600

Medium voltage network

299 700

Low voltage network

417 000

Table 2 shows the number of electrical energy consumers in Poland by individual voltage levels and the volume of energy supplied to these consumers. The big disproportion of the number of small and big consumers, with their total number of over 16 million, is worth noting. Tab. 2. Number of consumers and volume of energy by supply voltage level according to the data for 2007 [1] Voltage level consumers at HV consumers at MV consumers at LV TOTAL

Number of consumers [number] [%] 287 0,0 28 988 0.2 16 005 000 99, 8 16 034 275 100,0

Energy [GWh] 27 064 39 881 50 705 117 650

[%] 23 34 43 100

Fig. 1 and 2 show, respectively: share of consumers at individual voltage levels in total number of energy consumers and distribution of the supplied energy among consumers connected at various voltages.

Abstract The article presents an analysis of the possibilities of reducing power and energy losses in MV distribution networks by the use of the most popular non-investment method, that is optimal network conﬁguration, also called optimization of partition points. The article begins with a characteristic of distribution networks, structure of electrical energy consumers and a classiﬁcation of losses in distribution networks. Losses in real, wide-area MV voltage networks were analyzed.

The problem of partition points optimization in a network was presented. The methods of partition points optimization and some Polish tools for making such calculations were reviewed. The results of performance of the tools on an example of a real wide-area network were compared. The article ends with some remarks on practical aspects of calculating partition points in big networks, with special emphasis on various constraints in location of partition points.

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

The drawings indicate that the proportions of the energy consumed by individual groups of consumers are totally different than their quantitative distribution, that is a very small number of huge and big consumers of 110 kV voltage and MV consumes considerable volume of energy compared to the energy consumed by a great number of low voltage consumers. 0.0%

0.2%

99.8%

Consumers at HV

Consumers at MV

Consumers at LV

Fig. 1. Share of consumers at individual voltage levels in total number of electric energy consumers

Consumers at HV

Consumers at MV

Consumers at LV

Fig. 2. Energy supplied to end consumers at individual voltage levels

2. LOSSES ALLOCATION IN DISTRIBUTION SYSTEM Energy ﬂow through electrical power grids is always accompanied by losses. They are connected with current ﬂow through its individual elements. Table 3 presents distribution of the total of technical losses in distribution network by their individual types and elements of the network based on [2.] The data provides some information on areas of losses allocation in the distribution system. Tab. 3. Average technical losses in elements of distribution networks in [%] of their share in total technical losses [2] No

Type of losses

1. 2. 3. 4. 5. 6.

Load losses in 110 kV network Load losses in MV network Load losses in LV network No-load losses in MV/LV transformers Load losses in MV/LV transformers No-load losses in transformers 110/LV Total 1÷6 LV meters Load losses in 110/MV transformers LV wiring system Leakage conductance losses in MV network Leakage conductance losses in 110 kV network In 110 kV capacitors No-load losses in MV/MV transformers In MV capacitors IN LV capacitors Load losses in MV/MV transformers

7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

Share in total losses [%] 36 22 16 9 5 4 92 2.8 1.6 1.3 0.9 0.6 0.5 0.3 0.1 <0.1 <0.1

Leakage conductance losses in LV network

<0.1

Total 7÷17 TOTAL 1÷17

8 100.0

The first 6 items of the table cover 92% of technical losses of energy, whereas the remaining 11 items refer to 8% of the losses. The first three items show load losses in 110 kV, MV and LV networks. Such an order can be explained by the volume of energy flowing through networks of individual voltage levels. Transformation to lower voltage level refers to smaller and smaller volume of energy, due to the existing demand of consumers of the given voltage level (Tab. 2 and Fig. 2).

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

3. POWER LOSSES IN MV WIDE-AREA NETWORKS Some results of the analyses made on big MV distribution networks are presented below. The networks of eight electrical power regions, located in southern part of Poland, were investigated. Table 4 presents parameters of the networks, their peak load and load power losses in MV lines. The losses were calculated by the use of software for calculation of power ﬂow, by the use of detailed network models and estimation of loads of individual MV/LV transformer stations. Regions A – D have networks working at 20 kV, which is less popular in Poland. Power losses at peak load in the analyzed networks are at the level of below 1%. More detailed analysis of the networks of the regions A – D is presented in the further part of the article, devoted to practical aspects of optimization of partition points in wide-area networks. Tab. 4. List of parameters of MV wide-area networks and power losses occurring at peak load

Region’s name Region A Region B Region C Region D Region E Region F Region G Region H

Nominal voltage Number of MFP of the network [kV] 20 20 20 20 15 15 15 15

[pieces] 6 7 7 7 5 7 5 6

Number of MV/LV stations

Total length of MV network

Load at peak

Power losses

Relative losses

[pieces] 889 542 991 1157 582 1124 885 1028

[km] 969 520 1048 1277 511 1079 862 938

[MW] 64.69 55. 41 60.19 61.04 44.98 72.79 62.37 45.34

[kW] 578.6 239.8 349. 4 497.7 948.3 1182.6 1046 902

[%] 0.89 0. 43 0.58 0.82 2.11 1.62 1.68 1.99

Regions E – H operate at the most typical in Poland nominal voltage of MV, that is 15 kV. Their power losses level, presented in Table 5, is from ca 1.6% do 2.1%. The quoted loss ratio does not provide information on the losses in individual circuits of the network. The analysis whose results are presented in Fig. 3–5 was made to illustrate losses distribution and their differences in individual circuits. The networks of the regions E – H include 202 circuits of very different parameters, that is: total length, wire cross section, number of stations fed and peak load. They include short cable lines of urban networks, feeding a few MV/LV transformer stations, as well as wide-area circuits of rural network of the length of a few tens of kilometres, feeding a very big number of stations. The following diagrams present: • Fig. 3 – relative power losses in the lines, depending on their peak load • Fig. 4 – relative power losses in the lines, depending on their total length • Fig. 5 – relative power losses in the lines, depending on the number of MV/LV stations fed.

Relative losses [%]

The presented diagrams provide information on losses distribution and their considerable differences in individual circuits of the network.

Loads [kW]

Fig. 3. Relative power losses in 202 MV circuits (Regions E – H) as a function of their peak load

Total length [km]

Fig. 4. Relative power losses in 202 MV circuits (Regions E – H) as a function of their total length

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

Relative losses [%]

Fig. 5. Relative power losses in 202 MV circuits MV (Regions E – H) as a function of the number of MV/LV stations fed

Number of stations [pieces]

4. OPTIMIZATION OF PARTITION POINTS – A PRESENTATION OF THE PROBLEM Optimization of partition points is one of the basic activities of non-investment character, leading to reducing losses in a distribution network. MV distribution networks are built as closed structures, but they operate in open conﬁguration. Points of division which unambiguously determine to which circuits individual MV/LV stations belong are called partition points. The task of optimization of partition points consists in selecting network division points in such a way as to obtain a system characterized by the least total load losses. Solving such a problem for a real network, e.g. for one distribution region, comes down to solving the problem of minimization of a function of many variables, most often with constraints. It usually requires application of relevant tools and algorithms due to the size of the problem (number of variables) and the structure of the system (considerable number of mutual circuit connections). As mentioned above,in rural wide-area MV network, consisting of from a few tens to a few hundreds of nodes (stations), ﬁnding optimal – in terms of minimum power losses – partition points is not easy. Fig. 6 presents an example of power losses in a double-feed distribution line, depending on the partition point. Power losses are the smallest for the partition near the point of the lowest voltage. 9.8

9.3

Power losses [kW]

8.0 6.7 5.7 4.7 4.0

3.3

5. 4

3.7 2.8

2.7

2.9

Number of partition points

Fig. 6. Power losses in a double-feed distribution line, depending on the partition point of the line

Obtaining the effect in the form of reducing losses by changing partition points requires speciﬁed technical and organizational activities, which involves relevant costs. If a change of the line partition requires purchase and installing of new switches, the costs can be calculated the following:

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

(1)

where: Kro – total cost of purchase and installing of switches; Ko – investment cost of one switch; Kmi – cost of installing a single i-th switch; no – number of installed switches. The cost of installing a single switch takes into consideration the costs of labour and the costs of transport:

Kmi = kg tBR lBR + kkm lkm

(2)

where: kg – cost of one work hour of an employee; tBR – employee work time devoted to installing a single switch; lBR – number of employees; kkm – cost of one kilometre of transport; lkm – length of transport route. If changes of partition points are made in a network equipped with switches in each point in which it is possible to partition the line, then the costs come down to the costs connected with switchings in the network: (3) where: Krp – total cost of switchings; np – number of switchings made. Switchings will result in reduction of power losses by ∆∆P and of energy by ∆∆E. Profit Zp, resulting from reduction of power and energy losses, is calculated from the following: (4) where: ∆Pst, ∆Est – energy and power losses in the analyzed network before switchings; ∆Pno, ∆Eno – energy and power losses in the analyzed network after switchings; ∆∆P – reduction of power losses; τ – utilization period of maximum power losses; SS – fixed component of network charge (cost of power); k∆E – unit cost of energy in the network (price of energy + variable component of network charge). Effectiveness of the activities taken up can be assessed by calculating simple payback period (SPP) of the layouts made: (5) where: K – cost of purchase and installing of (Kro) or switchings (Krp). Example 1 The problem of partition points is considered in a model MV loop of electrical power network, feeding 120 transformer stations in 10 network loops of the following parameters of a single loop (line): • the sum of power of transformer stations installed in one line Stc = 5 800 kVA • maximum current flowing to loop: Imax = 120 A • energy introduced into network E = 28 059 kWh • length of a single line lt = 2 600 m • cross section of cable core: s = 120 mm2 AL. The calculations were made for the following additional data: • unit cost of energy losses (together with the variable component of network charge) k∆E = 0,20 PLN/kWh • unit cost of power losses (fixed component of network charge) k∆P = 80 PLN/kW/year

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

• number of employees lBR = 2 persons • cost of one work hour of one employee kg = 37 PLN/h • employee work time tBR = 4 h • length of transport route lkm = 10 km • unit cost of transport kkm = 3,0 PLN/km • number of switchings np = 8 • utilization period of maximum power losses τ = 2 100 [h/a]. It was additionally assumed that the transformer stations’ load is proportional to nominal power of the transformers and that the loop network has switches that enable making partitions in each section. In a loop network partition points can be located in various sections of the line It was assumed for the calculations that all loops are identical, but the partition points are located in different places. Table 5 presents the results of calculations of power losses in individual loops for a certain system of partition points, whose speciﬁcation is given in second line. Minimal losses that can be reached in the analyzed set of loops due to change of location of all partition points to optimal location are also given. Tab. 5. Power losses in loops Loop number

Partition point number (according to Fig. 6)

Power losses in loops (according to Fig. 6) [kW]

2.9

5.7

3.3

3.7

2.7

4.0

8.0

2.7

2.9

9.8

Total losses total in loops – existing state

[kW]

45.7

Minimal losses in loops (according to Fig. 6)

[kW]

27.0

Reduction of power losses ∆∆P

[kW]

18.7

If there are no technical constraints, then change of eight partition points in the analyzed network can result in losses reduction by ∆∆P = 18.7 kW. Simple payback period (SPP) (Formula 5) of costs of partition points dislocation in the network were calculated for the data adopted: • cost of switching in the network: Krp = np × (kg ×tR × lRB + kkm× lkm) = 8 × (37 × 2 × 4 + 10 × 3) = 2 608 PLN • proﬁt resulting from reduction of power and energy losses: Zp = ∆∆P × (SS + k∆E × τ) = 18.7 × (80 + 0.2 × 2 100) = 9 350 PLN • simple payback period: SPP = Krp/Zp = 2 608/9 350 = 0.28 years (3 months and 11 days). Average value of losses reduction per one switch-over is obtained by dividing the volume of losses reduction by the number of switchings needed to achieve it: δ∆P = ∆∆P/np. Fig. 7 presents dependence of simple payback period of costs on power losses reduction due to making one switch-over in the network, calculated for various values of utilization period of maximum power losses. Payback of layouts connected with change of partition points in the analyzed example depends on the utilization period of maximum power losses and unit power losses reduction per one partition point δ∆P. It follows from Fig. 7 that for the networks technically prepared for making partition points in any transformer station and for the value of losses reduction per one partition point δ∆P ≥ 1 kW/partition point, the costs connected with change network partition are returned after ca 1 year.

Simple payback period [years]

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

Proﬁt on power losses per one partition point [kW]

Fig. 7. Simple payback period of switching costs in the network, depending on average value of losses reduction ΔΔP, per one partition point for various utilization periods of maximum power losses

For loop networks or spindle type of networks and for the networks that can be reduced to such structures, calculations of power and energy losses can be made by the use of a spreadsheet – it is not necessary to use specialized software. A spreadsheet enables calculation of losses for the existing work conﬁguration and selection of conﬁguration of partition points matching minimum losses.

5. REVIEW OF METHODS AND TOOLS FOR OPTIMIZATION OF PARTITION POINTS Many methods for reduction of energy and power losses by proper selection of partition points have been developed. Heuristic methods, which enable analyzing networks of a big number of nodes have been applied in practice. SIEĆ, DRZEWO and STROP software can be examples of such solutions. The formula 3I2R is used in the methods of SIEĆ, DRZEWO, STROP software to calculate power losses. Each of the methods makes use, in various forms, of the following data: • the analyzed network data • information on network connections system • number of network sections • length of individual sections of overhead and cable lines • cross sections of cables and overhead wires • network nodes data • number of nodes • loads of peak active and reactive power of each of the nodes • utilization period of maximum power losses or load curve (step curve) to calculate energy losses • catalogue data (enabling selection of network elements parameters) • catalogues of overhead lines • catalogues of cable lines • catalogues of transformers. SIEĆ software The problem of optimal division of MV distribution network in SIEĆ software is solved in two stages [3], [4]: Stage I Initial solution is obtained in the ﬁrst stage. In the nodes there is only active power for peak load, and the network branches are mapped only with resistances. The same voltages in feed points are assumed. At this

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

stage, partition points are determined based on the results obtained from multiple (iterative) calculations of active power flows according to simplified Newton’s method. Total power losses are the minimized objective function. Stage II Adjustment of network partition obtained in stage I is made. In this calculation model, branches are mapped with longitudinal and transverse conductivities. Distribution of node loads (active and reactive load) is mapped by the use of step curve. Radial configuration in the first step is the starting point in second stage. Multiple iterative calculations of power flows in the network enable gradual modification of the initial configuration, till optimal configuration is obtained. The sum of energy losses is the minimized objective function in the second stage. SIEĆ software system consists of BAZA software and ROZA and REGA subsystems. BAZA software is used to create sets of data. ROZA subsystem is used to process primary data, to calculate power flows and short circuit power and to determine optimal partition points in the network, taking into consideration optimal assignment of lines to buses in two-system stations. Using the sets of node and branch data for individual MFP, REGA subsystem determines parameters of voltage regulators of transformers in MFP and location of tap changers of MV/MV and MV/LV transformers. Diagrams of radial network, together with calculations results (of flows, short circuits and optimization of voltage levels) can also be developed by the use of REGA subsystem. SIEĆ software enables making calculations for a network of practically any number of nodes and branches. The sets of node and branch data can contain any number of elements (e.g. network modelling by 10 000 nodes requires ca 4 MB of RAM). Further information on SIEĆ software can be found in literature [3], [4]. STROP software STROP software [5] optimizes configuration of partition points according to adjusted Rosenbrock algorithm [6]. Optimal location of partition points in the network is specified with the view of minimum losses of active power. Branches are reduced to concentrated loads, connected in proper nodes of the mains and are not subject to the process of optimization of partition points. Rosenbrock’s method [6] belongs to the group of non-gradient methods of simple search. In this method, objective function is examined (minimum of power losses) only in one or two points in the direction of the search (meeting the technical requirements). The way of selecting the points is determined at the beginning of each iteration. The essence of modifications of Rosenbrock method in STROP software comes down to controlling the length and the sense of the step (understood as a vector) and to imposing on the objective function a penalty for a solution outside the search direction. Each iteration in Rosenbrock method consists in making trial steps in all possible search directions. If reduction of the value of objective functions is obtained (power losses reduction) as a result of making a trial step, then the step length in increased. Otherwise, the step length is shortened and its sense is changed. In terms of calculations related to MV network according to [5], STROP software does the following: • calculation of power losses in the analyzed network • location of the capacitor unit of the given power in the line, with regard to minimum power losses • optimization of power of capacitor unit and its location in the line, with regard to minimum power losses • analysis of feed voltages in feed points of MV network • calculation of voltage levels and drops and determining regulation zones of MV, LV transformers in normal work conditions • short circuit calculations in normal work conditions of the network • calculations of voltage levels and drops in reserve state • short circuit calculations in reserve state of the network • optimization of partition points in the network (minimum active power losses) • determining feed variants in the case of a failure in the line (if there is technical capacity for such feed). In STROP software, the maximum size of the network, understood as a single set for calculations, can include: 90 main feed points – MFP (power supply units), 1 000 lines, 5 000 nodes, 5 000 line (in the mains of the network, not more than 3 500 line sections). Further information on STROP software can be found in [5].

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

DRZEWO software The method of Simulated Annealing – SA [7], [8], [9] was used for optimization of partition points in DRZEWO software. Power losses in the network were adopted as the economic criterion of selecting the optimal variant. Let us assume that the initial solution (e.g. operation configuration applied by the services of the given region) of ∆P1 power losses (Fig. 8) is known. The solution can be enhanced if e.g. gradient algorithm is used: • in each iteration, there is a randomly selected solution (network configuration) in the environment of the current solution • only the solutions of the losses lesser than in the previous solution are accepted. The possibility of getting stuck in the local optimum is the disadvantage of such an algorithm. For the example from Fig. 8, starting from the point (of the network configuration) of ∆P1 losses, using the gradient method, calculations will end in the local optimum (network configuration of the losses of ∆Pmin²). Power losses ∆P

conﬁgurations

Fig. 8. Set of possible network conﬁgurations of various power losses

In the algorithm of “stimulated annealing” it is possible to accept solutions of higher losses than the ones obtained so far. Proceeding according to SA algorithm comes down to the following rules: • change of ∆∆P losses as a difference of the current solution and last accepted one is calculated in each iteration step • if losses are reduced (∆∆P < 0), then the solution is accepted • increase of losses (∆∆P > 0) does not result in direct rejection of the calculated network conﬁguration; it can be accepted if the following condition is satisﬁed:

r < exp(–δΔP / T )

(6)

where: T – denotes a parameter simulating the temperature expressed in loss units; r – random number of uniform distribution from the interval (0;1). A calculation algorithm constructed in such a way enables accepting a solution of ∆P3 losses (Fig. 8), despite ∆P3 > ∆P1. It is possible to obtain a solution of ∆Pmin4 of power losses, which for the presented set of solutions is a global minimum. If parameter T, which in real physical systems represents temperature, is decreasing, starting from the adopted maximum value and according to a specified rule, then the described process is analogous to do annealing (cooling, tempering) of metals in crystallization process [8]. In DRZEWO software, switching off the line feeding a randomly selected network node is the element changing the network configuration, the result being – a fragment of an isolated network. Then the disconnected node is fed from all live nodes. Objective function is calculated for each new configuration (with changed locations of partition points). If the new configuration has smaller losses, it is accepted, otherwise a solution according to the modified rule is adopted for further considerations (6). DRZEWO software is designed for optimization of development of MV distribution network of a tree structure. Calculation of optimal partition points in the network is an extra option. The software enables calculations for distribution networks of tree structure of practically any number of nodes and branches. A commercial version of the software has not been developed.

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

6. COMPARATIVE CALCULATIONS OF OPTIMIZATION OF PARTITION POINTS IN REAL NETWORK BY THE USE OF VARIOUS TOOLS Example 2 A real network of one of electrical power supply regions was chosen for optimization of partition points in MV distribution network. It is a network located in mixed rural and urban area, in which most circuits have an option of double-feed. Number of receiving nodes in the network is 970, and the number distribution nodes – 648. The network consists of 1 793 sections, of which 73% are overhead sections, and 27% - cable sections. Power and energy losses in the network conﬁguration before and after optimization of partition points as wells as and proﬁt due to power and energy losses reduction were calculated. The calculations were made for the following data: • operating voltage of the network Ur = 15,75 [kV] • utilization period of maximum power losses τ = 3 106 [h/a] • unit costs of power losses Ss = 36.36 [PLN/kW/a] • unit costs of energy losses k∆E = 0.25 [PLN/kWh/a]. The calculation results are presented in Table 6. Effectiveness of change of partition points in the network was calculated based on the results obtained. The costs of installing switches (adopted cost of a switch ko = 4 000 PLN, other data for the calculations, as in example 1) and simple payback period costs were calculated form (1)÷(5). The calculations are given in Tab. 7. Tab. 6. Comparison of results of calculations of annual energy and power losses for the network of the region Power losses [kW]

Energy losses [MWh]

before optimization

after optimization

difference

before optimization

after optimization

difference

Proﬁt [thousand PLN]

DRZEWO

571.1

504.1

67.0

1773.8

1565.7

208.1

54. 44

SIEĆ

612.1

515.6

96.5

1901.2

1601. 4

299.8

78.64

STROP

582.1

461.1

121.0

1808.0

1432.2

375.8

98.14

Software name

Tab. 7. Simple payback period costs of installing disconnecting switches in the network

Software

Number of partition points in the network as it is now [pieces]

Number of proposed changes of network partition points location [pieces]

Number of new switches [pieces]

Investment cost of switches [thousand PLN]

Simple payback period of costs [years]

DRZEWO

248

4.7

SIEĆ

308

4.1

STROP

284

3.0

The literature provides descriptions of other methods of optimization of partition points: cycles and penalties [10] and based on evolution algorithms [11]. Paper [11] presents a comparison of results of the calculations made by the use of cycles and penalties method and an evolution algorithm for examples of electric power networks consisting of a small number of nodes and lines. Based on the analyses made, one can formulate the following general conclusions: 1. Calculation of optimal partition points with regard to minimum energy and power losses in big networks of multi-meshed structure requires application of specialist software. 2. Each of the software - DRZEWO, SIEĆ, STROP can be used for optimization of partition points with regard to minimum power losses in big MV distribution networks.

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

3. The results of calculations of power losses generated by the software differ. The differences are due to: • application of different methods of looking for optimal partition points in the network • way of calculating loads in individual transformer stations. 4. In the networks of regular structure (spindle, loop) and the networks that can be reduced to such structures, optimization of partition points with regard to minimum power losses can be made by the use of a spreadsheet.

7. PRACTICAL ASPECTS OF OPTIMIZATION CALCULATIONS IN WIDE-AREA NETWORKS The results of the calculations and the experience gained during optimization of partition points in medium voltage networks in a few distribution regions are presented below. STROP software, developed in Częstochowa University of Technology, was used to calculate optimization of partition points [5]. The software enables, inter alia, making calculations of power flow in electrical power distribution networks, optimization of partition points location, and voltage calculations. Developing a proper model of the considered electrical power network is the basis for losses analysis and their optimization. It was achieved in a few stages mentioned below: • development of a precise model of the network structure – the model consists of all the existing sections of medium voltage lines, with specification of the ways of their mutual connection and the parameters of a substitute diagram (resistance, reactance, susceptance); the model has also the information on all partition points of the network in the existing configuration • estimation of loads on MV/LV transformer stations – determining the active and reactive load demanded by individual transformer stations at peak load, based on available measurement information coming mainly from MV lines in MFP and the information on the load levels in the stations • equipping the structure model with node loads – assigning the loads of individual transformer stations to proper nodes in network model. Such a model of an object is a starting point for making calculations of the configuration of the network in the existing configuration, and then for optimization of location of partition points. The calculations were made for four medium voltage distribution networks. Each of the networks covered the area of one distribution region. Table 8 presents the data characterizing individual networks. Tab. 8. Parameters characterizing the analyzed distribution networks

[km]

Average cross section of the network [mm2]

889

969

101

542

520

991

1 048

135

1 157

1 277

107

Nominal voltage of the network

Number of MFP

[kV]

[pieces]

Number of MV/LV stations [pieces]

Region A

Region B

Region C Region D

Region’s name

Total length of MV network

Number of partition points [pieces]

The table presents parameters characteristic for the network, that is: nominal voltage, number of feed 110kV/MV stations, number of MV/LV stations, total length of MV network, average network cross section and the number of partition points. The calculations of load flows and power losses in the existing configuration were made based on the network models and mapping of loads of all MV/LV stations. The results of those calculations are presented in Table 9, with values of power losses in kW and value of relative losses with reference to demand power. Analyzing the volume of power losses appearing in the medium voltage networks of the considered electrical power regions, one can say that already in the existing configuration they are at a very low level. It means that relative losses ratio referred to demanded power, is between 0. 43% and 0.89%. Such a low value of losses results from a number of factors, which include:

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

• high value of nominal voltage of distribution networks • high cross section of the network, whose measure is the mean value of the line cross section given of in Table 9 • favourable structure of the network, namely small number of circuits of big lengths • low load in comparison to transmission capacity. Then the optimization calculations connected with change of the configuration of the network, the so called global optimization, were made. Global optimization means determining configuration of the network of minimal power losses, which is subject to any constraints connected with location of partition points. It means that each partition point can freely change its location, and its target location can be in any selected section of the network. But one must note, however, that such a solution of the network configuration is possible only theoretically. In practice, there are many factors constraining both the possibility of moving some partition points and constraining the potential new locations. These issues are discussed in more detail in the item on constraints of location of partition points. Calculations of global optimization enable specifying potential, maximum possibilities of reducing losses that can be achieved by network reconfiguration. It means that the calculations set upper effectiveness limits of such activities. The results of the calculations of power losses in the optimally configured networks (without any constraints) for individual distribution regions are presented in Table 9. The values of losses in kW and percentage level of losses after global optimization in comparison with losses in the existing configuration. Table 9. Results of calculations of power losses in the existing configuration and after global optimization

Region’s name

Peak load with active power

Power losses in exiting conﬁguration

Level of losses with referPower losses after global optimizaence to existing conﬁguration tion [kW] [%]** 310 54

Region A

[MW] 64.69

[kW] 578.6

[%]* 0.89

Region B

55. 41

239.8

0. 43

199.9

Region C

60.19

349. 4

0.58

282.5

61.04

497.7

0.82

380. 4

Region D * **

the ratio was calculated with reference to peak load active power the ratio was calculated, referring losses in optimized conﬁguration without constraints to power losses in the existing conﬁguration

The percentage ratio given in the last column of Table 9 is the lowest for region A - 54%. It means that in this region reconfiguration can bring, potentially, the biggest effect. In the other areas (the ratio from 76% to 83%), the existing configurations of the network are much closer to global optimum. But the real possibilities of losses reduction due to reconfigurations will result from the detailed analysis of the exiting constraints of division point locations. An analysis of the configurations in real conditions in which wide-area distribution networks operate and of the conditions determining the work configurations of networks indicates that in practice there are many factors that make the locating of partition points of the network in any place impossible. Constraints of partition point locations can be divided into two basic groups: • determining – constraints due to the necessity of having partition points in strictly defined locations of the network – some partition points of the network have pre-defined locations and cannot be moved • limiting – constraints connected with lack of possibilities of locating divisions in any section of the network – they limit the possibilities of changes of location for the partition points for which the location can be changed. The existence of determining constraints is caused by the factors of legal or technical character, which include: • binding electrical energy supply and sales contracts with the consumers that have their own transformer stations, paying for two power supplies • saving proper configuration of feeding substations • proper operation of automatic transfer switch in MV and LV network • different ways of operation of star points of 110kV/LV transformers

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

• borders of operation of the areas of the network and points of settlement measurement of electrical energy • other issues connected with e.g. separating systems to provide for proper cooperation of sources with MV distribution network. The existence of limiting constraints is due to the factors of technical and operational character, which include: • lack of switches in some sections of the network • rated current of existing switches • difficult access to a given point of the network • no access to stations at each time of the day and night • other issues, e.g. organizational, connected with ownership structure of elements of distribution network. The presence of determining constraints means that some locations of partition points cannot be changed. It results in decrease of the number of variables in the task of optimization of the given distribution network. And the presence of limiting constraints means that not all the indications for moving partition points, obtained as a result of optimization procedure, can be fully implemented. In such cases, they are implemented in the section that is the closest to the optimal section, where it is possible to make the division. Both leaving a certain group of partition points outside optimization procedure and imprecise moving of some movable partition points results in increased power losses in the configuration with constraints, compared to globally optimized configuration. Many optimization calculations for the networks of individual regions - A to D were made taking into consideration the above mentioned constraints concerning location of partition points. Such calculations enable: • indicating implementable changes in network configurations • possible identification of optimal location of some partition points • identification of the needs of installing new switches. The selected results of the calculations are presented in Table 10. It contains information on the number of the existing constraints, the number of optimally located partition points, the values of power losses in optimized configurations, taking into consideration all the constraints and changes of power losses compared to power losses in the existing configurations. Tab. 10. Results of calculations of power losses after optimization of network configurations, taking into consideration the constraints Total number of constraints

Number of optimally located partition points

Power losses in optimized conﬁguration with constraints

Losses reduction compared to the existing conﬁgurations

[%]*)

[kW]

[%]

Region A

543.1

6.1

Region B

237.9

0.8

Region C

341.7

2.2

Region D

466.8

6.2

Region’s name

)

relative values calculated in relation to the total number of partition points in the given distribution region

By analyzing the results presented in Table 10, one can formulate the following remarks: • in practical calculations of configuration optimization of distribution networks one should be aware of the existence of a considerable number of constraints of location of partition points; in the case of the objects discussed, the constraints referred to from 50% to even 70% of the total number of partition points • a considerable number of optimally located partition points (from 21% to 36%) among the variables whose location can be changed is also significant; it can mean that the services are well aware of the loads and that they do take care of maintaining proper configuration of the network • reconfiguration resulted in reduction of losses from 0.8% to 6.2%; the effect, translated into savings on annual reduction of energy losses, is estimated at ca 18 000 PLN to 21 000 PLN for the regions D and A • the existing configurations of the distribution network is, to a great extent, determined by the factors of legal and technical character.

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

The effectiveness of losses reduction obtained due to optimization of partition points obviously depends on individual features and properties of the distribution network under analysis. Better effects can be expected in the networks of lower nominal voltages (e.g. 6 kV), long circuits and considerable load. The results of the research of Edward Siwy from Silesian University of technology [12] on conﬁguration optimization of MV distribution networks indicate that effectiveness of such operations can be high. Table 11 presents effects of optimization of partition points in 3 distribution networks. Additionally, using the results of calculations of power losses for a different number of constraints in the locations of the partition points of the analyzed regions A, B, C and D, a diagram illustrating the dependence between power losses and the number of existing constraints was developed. The diagram is presented in Fig. 9. The number of constraints was expressed in [%] in relation to the total number of partition points. Power losses were expressed in relative units in relation to the losses occurring in the conﬁguration without constraints. Tab. 11. Possibilities of reducing energy losses after optimization of partition points in MV urban networks in selected areas (according to [12]) Number of MV/LV stations [pieces] 600 780

Reduction of losses [%]

Estimated savings [thousand PLN/year]

500

130

550

430

Relative increase of losses [-]

430

Length of MV lines [km]

Number of constraints [%]

Fig. 9. Dependence of power losses as a function of the number of constraints of partition points locations of the network

The diagram shows that in each case the increase of the number of forced locations of partition points results increase in power losses in the network. The dependence is different for each network area. Change of power losses per one partition point, resulting from keeping its location or impossibility of its free movement can be, as the drawing indicates, very different. Each time, determining those values requires calculations with the use of the network model. It can be interesting to ﬁnd out about the circumstances causing a signiﬁcant increase of losses due to maintaining a small number of partition points in their original locations. An MV generation unit of considerable power, connected to the distribution network, cooperates with the region A network. Due to continuous changes in voltage conditions in the network caused by changes of the operational status of the unit, a separate feeder must be maintained connecting the generator with the power substation (MFP).

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

Another case encountered in practice is that of a network of significant power losses, whose configuration is forced by a non-uniform ownership structure of the network. In this case, power losses reduction would require feeding of some of the consumers via a substation, which is not owned by the distributor. The costs of potential transit would not be covered by the profit resulting from losses reduction. The considerations presented above referred to cases of forced location of partition points whose change would significantly reduce losses. In the other situations, the change of power losses per one partition point with constraints was much smaller. The issues presented above referred to constraints of determining character. The constraints from the other group (the so called limiting constraints), concerning the impossibility of free location of movable partition points is also worth mentioning. In the situation in which the indication of the optimization procedure referred to the section in which, for various reasons, the division could not be made, a division in the closest point was proposed, with calculation of the differences of losses resulting that change. The differences were usually small or simply insignificant. In particular, in no case a change of losses that would justify install a new switch in the network was observed. Optimization of configuration of distribution network is one of the most often mentioned ways of no-investment reduction of power losses. A solution of such a problem for a big real network requires application of adequate calculation tools and developing the network model. Proper estimation of loads of individual transformer MV/LV stations is one of the significant problems. It is due to the lack of measuring devices in distribution network. The load data of individual lines, results of periodical measurements in MV/LV stations and the expertise of operation staff of the distributor were helpful. Four distribution regions of typical size, of typical scope of network and average power demand were analyzed. The small power losses in the existing configurations can be explained by the high value of nominal voltage, considerably big average cross section and a compact structure of the network. Calculations of the configuration optimization made without taking into consideration constraints enable initial identification of maximum effects of a network reconfiguration. But before detailed analysis of the constraints of individual partition points occurring in a given configuration is made it is not possible to assess the scope of losses reduction that can occur due to practical implementation of the change of configuration of the network. Constraints of location of partition points can be of twofold character: determining or limiting. In the first case they come down to the necessity of maintaining partition points in strictly defined locations of the network, and in the other one – they do not allow totally free location of the partition points whose location can be changed. Those constraints are due to formal-legal or technical-operational reasons. The presence of limitations on the location of partition points which are among the constraints of optimization negatively affects the level of the achieved optimal solution. A configuration with constraints always has bigger power losses than a configuration without constraints. The presented examples indicate a considerable number of limitations in the practical tasks of reconfiguration of wide-area distribution networks – the constraints apply to more than 50% of existing partition points. Also noteworthy is the considerable number of partition points located optimally in the initial configuration (from 21% to 36%). The analysis and possible changes of configuration of the network gave an effect in the form of losses reduction up to ca 6% at peak load. The effect can be seen in savings on lower energy losses, which annually reach the amount of 18–21 thousand PLN. So significant savings on energy losses can be made even in a network of small losses before reconfiguration and a considerable number of constraints. As Table 11 shows, such savings can be of much higher value in other distribution networks. The potential for losses reduction per one partition point with constraints varies considerably and requires individual calculations with the use of the network model. The reasons for maintaining unfavourable locations of partition points of big losses reduction potential can be complex and vital for the network.

Aleksander Kot; Jerzy Kulczycki / AGH University of Science and Technology in Kraków Waldemar L. Szpyra / AGH University of Science and Technology in Kraków

8. CONCLUSIONS Optimization of partition points is one of the basic ways of non-investment reduction of losses and a subject of numerous publications, in Poland as well as abroad, devoted to losses reduction in distribution systems. The essence of optimization consists in finding such configurations of MV network, determined by the given location of partition points of the network, so as to obtain a configuration characterized by the smallest power losses. For simple network structures, such as a loop or a spindle, optimization calculations can be made independently for each variable (each partition point), e.g. by the use of a spreadsheet. More complex configurations (more connections, more meshed) require adequate calculation techniques and specialist software. Each of the software, that is SIEĆ, STROP and DRZEWO, can be adapted to optimization of partition points with regard to minimum power losses in big MV networks. The differences between the solutions obtained for the same network by the use of different tools are due to application of different algorithms of looking for an optimal solution and the way of calculation of loads of individual MV/LV transformer stations. Practical implementation of optimization of configuration of the network must take into consideration various constraints connected with the impossibility of changing the location of some partition points and incomplete set of possible allocations determined by the existence of switches only in selected sections and access reasons (e.g. access to some partition points). For the locations of partition points forced by legal issues (consumer pays for two supplies), real costs of maintaining the division in the given point of the network should be calculated and transferred in the fixed component of power charge paid by the consumer. The effectiveness of reconfiguration operations that can be achieved in a real network surely depends on individual features and properties of the distribution network analyzed. Better results can be expected in the networks of lower nominal voltages (e.g. 6 kV), long circuits and significant load. The development of the energy market and the increased operational effectiveness of energy companies will probably stimulate distributors’ interest in non-investment reduction of losses in distribution networks. The modern IT power industry dedicated systems for network assets management and advanced measurement-settlement systems will be of significant assistance in analyzing optimal configurations of distribution network. Such IT and measurement systems will enable implementation of network configuration optimization with regard to minimum energy losses in a given time period, which is now hard or impossible to implement.

Possibilities of Losses Reduction in Medium Voltage Distribution Networks by Optimal Network Conﬁguration

LITERATURE 1. Folder: Electrical Energy Statistics 1997–2007, Ministry of Economy of the Republic of Poland www.mg.gov.pl. 2. Kulczycki J. (ed.), Ograniczenie strat energii elektrycznej w elektroenergetycznych sieciach rozdzielczych, PTPiREE, Poznań 2002. 3. Harasimowicz L., Optymalizacja pracy sieci rozdzielczych średnich napięć, Materiały konferencji naukowo-technicznej – Straty Energii Elektrycznej w Spółkach Dystrybucyjnych, Poznań 17–18.05.1999, pp. 289–295. 4. Harasimowicz L., Suboptymalny podział dużych sieci rozdzielczych dla potrzeb eksploatacji, rozprawa doktorska, Instytut Energoelektroniki Politechniki Wrocławskiej, Wrocław 1992. 5. Czepiel S., Obliczenia optymalizacyjne i inżynierskie dla sieci średniego napięcia. Instrukcja obsługi programu STROP, Instytut Elektroenergetyki Politechniki Częstochowskiej, Częstochowa 1999. 6. Kręglewski T., Rogowski T., Ruszczyński A., Szymanowski J., Metody optymalizacji w języku FORTRAN, PWN, Warszawa 1984. 7. Brożek J., Kot A., Kulczycki J., Szpyra W., Bezinwestycyjne metody zmniejszania strat energii w sieciach rozdzielczych w pracach badawczych zakładu elektroenergetyki AGH, Materiały konferencji naukowo-technicznej – Straty Energii Elektrycznej w Spółkach Dystrybucyjnych, Poznań 17–18.05. 1999, pp. 264–277. 8. Chiang H.D., Jean-Jumean R.M., Optimal Network Reconfiguration in Distribution Systems, IEEE Transactions on Power Delivery, vol. 5, No 4, November 1990. 9. Mazur P., Ograniczanie strat mocy i energii w sieciach zamkniętych SN. Praca dyplomowa Wydz. EAIiE AGH, 2001. 10. Kujszczyk Sz., Nowoczesne metody obliczeń elektroenergetycznych sieci rozdzielczych, WNT, Warszawa 1984. 11. Helt P., Parol M., Piotrowski P., Metody sztucznej inteligencji w elektroenergetyce, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2000. 12. Siwy E., Żmuda K., Intensyfikacja wykorzystania sieci w spółce dystrybucyjnej, Przegląd Elektrotechniczny No 3/2009, pp. 243–246.

Sylwester Laskowski / ENERGA-OPERATOR S.A.

Authors / Biographies

Sylwester Laskowski Gdańsk / Polska Director of Regulation Policy Department of ENERGA-OPERATOR S.A., employed in the company since 1999. A graduate of Electrical Engineering Faculty of Gdańsk University of Technology (1999). He completed post-graduate course on energy company management in the conditions of development of Polish and international energy markets in Warsaw University of Technology (2002) and MBA course organized by Gdańsk Foundation for Management Development (2008). He has a diploma of completion of the course for supervisory board members in state treasury companies. He has focused on electrical energy market regulation issues since the beginning of his professional career. In his company he is responsible for all the regulation issues. He is an active member of Polish Society of Electrical Energy Transmission and Distribution, working on developing system regulatory solutions.

Regulation of Electrical Power Market

REGULATION OF ELECTRICAL POWER MARKET Sylwester Laskowski / ENERGA-OPERATOR S.A.

Power industry is a special sector of economy. It operates, to a great extent, based on the rules of a natural monopoly (network companies), and as such is not subject to market regulation mechanisms. Due to strategic significance and considerable impact on functioning of the entire economy, as well as due to living needs of people, governments of many countries aimed or are aiming at developing new rules that will create a substitute of competition in that sector. The state trying to affect behaviour of companies to make them more efficient, to protect customers against excessive price growth, is called regulation. The process of subjecting power industry to competition mechanisms in each of the states was carried out gradually and took various forms. Implementation of regulatory rules was spread over time because it was necessary to create relevant legal and regulatory framework. Also in Poland, where the history of power industry regulation is not long, creating the mechanisms substituting the market was a gradual process. It has not been completed yet, and is still undergoing various modifications.

THE TAMING OF THE MONOPOLY “Regulation – application of legal instruments specified by the Act, including licensing, in order to ensure security of energy supply, correct fuel and energy management and protection of customers’ interests”1. General availability of electrical energy, treating it as a common social good in confrontation with imbalance of impact power of consumers and suppliers, sellers and producers of electrical energy makes it necessary for the state to supervise this sector of economy. The aforesaid, and the impact of price changes of energy carriers on general condition of economy, by influencing e.g. inflation rate, makes it necessary to enable the state to influence companies through supervisory, ownership bodies, but mainly through legislation. The general level of supervision and control results from many factors and system solutions, serving the purpose of implementing the doctrines of economic policy of the state. The basic system solutions include all legislation (national parliamentary acts, EU directives) and detailed government assumptions, e.g. documents on assumptions of Polish energy policy. Electrical energy distribution companies obviously operate in the conditions of natural monopoly, thus having more opportunities to generate unjustified profits if there is not any control. That is why in market economy countries, which, after system transformations, also include Poland, it is very important to balance 1

Art. 3 item 15 of the Energy Law.

Abstract Thes article is an attempt to explain the essence of regulation. It presents its deﬁnition and the basic features that should provide for effective regulation. It includes a description of natural monopolies as the areas in which state control is necessary and inevitable. The criteria that should characterize a properly functioning, efﬁcient and effective regulatory system are another aspect mentioned in the paper, since meeting the criteria results in increased trust in the regulator’s activities. The problem of independence cannot be omitted. It is still a subject of discussions between the parties concerned. The institutions and communities calling for the

regulator’s independence are not in full agreement and are not fully convinced that it can be achieved in individual countries. There is not a strict interpretation of the notion of regulator’s independence but there are features that should surely characterize the activities of an independent regulator. Presentation of two regulatory systems is the last part of the paper. The system based on regulation of rate of return on capital, called cost regulation, and the system based on specifying a certain level of prices according to RPI – X formula, called incentive regulation are presented.

Sylwester Laskowski / ENERGA-OPERATOR S.A.

the power of energy companies and customers. It can be said that regulation is a sort of intervention of the state into the rules governing the economy. Such intervention comes down to exercising supervision, control of operation and specifying the rules of behaviour of the companies operating under natural monopolies, through legislative (national parliamentary acts, EU directives) and institutional regulations (Energy Regulatory Office). Regulation is there for the state bodies to counteract aspiration of the companies operating under monopoly to make high, excessive profits, in this case, at the expense of electrical energy consumers. The recent restructuring of energy companies, consisting in separating the operation that features signs of competition (electrical energy distribution and production) and the operation functioning under natural monopolies (electrical energy transmission and distribution), resulted in a sort of narrowing of the regulated area, in the strict sense of the term. Regulation means introduction of certain restrictions (rules) aimed at bringing monopolistic operation closer to market conditions. There is no direct impact of competition on behaviour of entrepreneurs, but the rules applied are to facilitate operation and development companies by influencing level of prices, which is closed related to the volumes of income made. One can risk a statement that already art. 1 item 2 of the Energy Law implies that regulation rules must function and why, as it says: “The purpose of the Act is the creation of the conditions for sustainable development of the country, energy security, efficient and rational use of fuels and energy, development of competition, counteracting negative consequences of natural monopolies, consideration of natural environment protection requirements and obligations stemming from international agreements and balancing the interests of energy enterprises and fuel and energy customers costs minimization.” In particular, the group of objectives, such as development of competition, which counteracts negative consequences of natural monopolies and protection of interests of customers, indicates the necessity of regulation activities. Integrated analysis of that group of the Act’s objectives is justified by the axiom that customers’ interests can be best protected by development of competition and limiting consequences of monopolies, leading to reduction of costs and prices. The monopoly has a character of a natural monopoly only in its part including operation by the use of a network2. The Energy Law and the executive documents based on the Act feature a few instruments serving the purpose of promoting competition and protection against consequences of monopolies, including: • establishing the institution of a regulator (Energy Regulatory Office) • licensing powers of president of Energy Regulatory Office • requirement to present tariffs for approval by “network” companies.

COMPETITION SUBSTITUTE IN AREAS OF MONOPOLIES Regulation – as indicated above – is a kind of state interventionism in operation of companies, according to clearly defined rules and competent institutions, by the use of using the tools that make up the regulatory system. Such activities are more and more often taken up when market mechanisms fail, and serve the purpose of balancing demand and supply in the economically justified distribution of benefits and costs. The mechanisms are also used when it is necessary to protect public interest, which is not subject market verification3. It refers in particular to, inter alia, electrical energy sector, which is an area heavily affecting the life of people and functioning of the economy of the state. It is due to the fact that in each developed country electrical energy plays a special role and is the basic source of meeting existence-functional needs of people. Due to the strategic significance of the product called electrical energy and of the service of supplying it, for a number of years it has been an area under strict control of the state and operated in the structures of natural monopoly. The monopolies date back to the time when structures of energy sector were being created and when the sector was being developed. They are also connected with establishing exclusivity on the side of providing supply services connected with energy supply4.

2 3 4

Baehr J., Stawicki E., Antczak J., Prawo energetyczne, Komentarz, Zakamycze 2003. Dobroczyńska A., Juchniewicz L., Zaleski B., Regulacja energetyki w Plsce, Warszawa – Toruń 2001, p. 12. Dobroczyńska A., Juchniewicz L., Zaleski B., op. cit. p. 13.

Regulation of Electrical Power Market

Nowadays, in line with the EU Member States wish to liberalize energy market, activities aiming at increasing competition in the biggest possible area connected with electrical energy or also, where it is not possible, at clear specification of regulation rules, which are a substitute of the market, are expected and performed. It can be seen that regulation of various forms has been in place almost since the very beginning of energy sector. It is due the fact that the authorities recognized the value and significance of electrical energy for the society and the economy. Existence and nourishing by the authorities the natural monopoly had for a long time been considered to be something obvious and optimal for the entire economy. There was an opinion that such a practice is of objective character. It was explained by lack of competition in the sector. But lack of competition had many negative consequences, both for those sectors, and the entire economy. In power industry the most significant consequences included: lack of pressure on rationalization of operation in the sector, that is lack of effective mechanism of efficient allocation of capital and labour and – mainly – using the characteristic for a monopoly price dictate, transferring all the consequences of such management to end users (also in the case when there were official prices)5. There were also other unfavourable things. The desire to eliminate or prevent them led to changes in the perception of monopolies in that from. Energy crises and drastic price growth of fuels and energy (the period of the so called oil shock of the 1970s) can be an example of negative consequences. Also the opinions about disastrously exploited conventional fuels, perceived by energy sector as barriers to economic growth, and lack of effective tools of protection of interests of customers were not insignificant, either. The changes forced by such a state of affairs had to be based on strong and stable foundations, using the authority and institutional resources of the state. The governments of many states decided to reject a strict monopoly, introducing, wherever possible, rules of market competition. Where it was not and is not possible to introduce market rules, formal and legal tools and solutions, called regulation, started to be applied. By definition, regulation is to be a substitute of competition in areas of monopolies. In the areas of competition, effectiveness of companies is forced by their desire to make profits. Competitive advantage is the objective of most businesses. The sooner it is reached, the bigger the initial profits of the company are. Obviously, (in the case of lack of further development) this advantage will be liquidated, and the desire to stay in the market will result in sharing the prior profits with the customers. The situation of effective competition occurs when none of the companies can make excessive profits (charge excessive prices) without losing a share of the market, and cost reduction is the only possibility of making bigger profits. The idea of operating in such a way gave rise to de-monopolization of energy sector and introducing rules of competition. For obvious reasons, competition mechanisms cannot be introduced into the entire energy sector. It is not rationally and economically justified to allow many entities to distribute electrical energy because each of those companies would have to develop its own grid infrastructure, which would obviously generate additional costs of functioning. Electrical energy generation and distribution are the areas in which competition rules are introduced (i.e. regulation is limited). In the case of electrical energy transmission and distribution, effective protection of customers against inefficient operations of companies can take place only by the use of the mechanisms supervised by a regulatory body. Use of combined market mechanisms and regulation of the areas under natural monopoly is the target model of exercising supervision.

SELECTION OF RULES VS. INDEPENDENCE OF THE REGULATOR Setting the framework of legislator activities in developing legal solutions so that the system might function effectively and efﬁciently is the main issue in creating a regulatory system in the state. Well developed and applied regulation rules are mainly to attain the following objectives: • protection of electrical energy customers against unjustiﬁably high prices for the services provided • stimulating regulated companies to rationalize costs of operation, by “forcing” increased effectiveness (it can be seen mainly at the stage of approving charge rates by specifying model costs of operation) 5

Dobroczyńska A., Juchniewicz L., Zaleski B., op. cit. s. 13.

Sylwester Laskowski / ENERGA-OPERATOR S.A.

• assuring adequate quality level of electrical energy and services provided • impact on assuring energy security of the country. A well functioning regulator should mainly show the following features: • stability of actins and decisions • objectivism • predictability • transparency. The regulator’s working according to the above mentioned rules can result in increased trust in his activities, both on the part of the participants of the system (customers, suppliers), and other entities that are interested in investments in energy sector. Following the rules is difficult due to the fact that in certain cases the governments may want to influence the decision making process and the decisions of the regulator. That is why – as shown above – legislators of individual countries introduce regulations serving the biggest possible independence of the regulator, so that changing political factors could not affect the regulator. The problem of independence of the regulator is still being discussed by the parties concerned. Even the institutions and communities promoting and calling for independence of the regulator are not in full agreement and sure whether that postulate can be made a reality. Governments are very unwilling to give up political control over operation of regulators, as most of the decisions made by them have a direct impact on the society, in the form of increased costs of functioning. Coming back to the core of the issue, it should be noted that in individual countries, communities and institutions there are disagreements as the principle of independence itself. There is not a clear interpretation of that notion as it refers to regulators, but one can name the elements that should definitely characterize activities of the regulator, so that he might not be charged with lack of independence. These activities include: • separating from and making independent of political factors (government forces) • keeping adequate distance to individual participants of the system, i.e. mainly customers and energy companies • Institutional independence, understood as a financial body other than the sources specified in the Act (e.g. licenses), by the participants of the system; it should be understood as, e.g. separate rules for employee remuneration. Due to the disproportions in the impact power of energy companies and customers; by definition the regulator exercises a definitely bigger “supervision” over operations of energy companies. That is why the following objectives can be attained: • protection of customers against undesirable operations of energy companies operating under natural monopoly • promotion of economic effectiveness to reduce cost impact on the prices of the services provided • protection of capital of investors (the private ones in particular) against political and economic decisions of governments. Regulation of energy companies is a complex process due to many internal (sectoral) and external (political) conditions. It should be noted that it is natural for governments to assure their influence on the decisions of the regulator, in particular when they refer to prices for the services provided. The history saw, even in regulation of Polish electrical energy sector, that the decisions made by the regulator were not based exclusively on economic effectiveness premises, but on the pro-economy ones, referring to, e.g. impact of energy and services price growth on the general inflation rate. One can say that artificial decrease of prices and rates for the services provided was connected with specified financial consequences for the regulated companies. Since the companies were owned by the state, the first phase of regulation did not bring any complications in the form of court trials. The growing liberalization and privatization of companies may result in the owners of the companies being less willing to accept politically driven operations. One must note here, however, that in Polish regulation developing over the years shows significant reduction of political impact on the decisions made. The state’s guarantees of clear rules of functioning of the regulator, its being immune to current political needs is the necessary conditions for attracting private investors, who will not be afraid of what is going to happen with the investments they made. It is even more risky since investments in energy sector are long-term

Regulation of Electrical Power Market

investments, both in terms of construction and operation. If investors operate in stable and clear regulatory environment, their decisions are less risky, and the cost of the capital engaged is definitively lower. But due to the possibilities of changes in the environment, both market and technological ones, operations of the regulator must be sensitive to the changes and balanced. In the properly functioning regulatory system there should be limitations of both political factors affecting the regulator and the regulator himself. It is also important that the framework of the regulator’s operation and his independence in decision making should make it impossible for him to take arbitrary, unrestricted and irrevocable decisions. In the light of the above, it is necessary to specify the degree of decision making freedom of the regulator. The powers of regulators in individual countries and regulation areas (economy sectors) differ. There are regulatory systems based on great decision making freedom of the regulator, e.g. in USA, or the ones in which regulation is introduced through many legislative solutions restricting the freedom. Most of the regulation solutions is somewhere between the extremes. It is of utmost importance to specify the scope of decision making freedom, by specifying the competences of individual institutions, which will minimize the possibility of abuse. It is natural to conclude that ministers cannot be regulators as then it is impossible to avoid political influence. Furthermore, due civil servants remuneration systems in most countries it would be impossible to keep highly qualified specialists. So it is ideal to establish a body of institutional and partially financial autonomy, with guaranteed term of office. Establishing an independent regulator (body) is not easy the states that have a short tradition of independent public institutions. To sum up, the following are guarantees of the regulator’s position of a strong and reliable institution: • independence • adequate isolation from political pressures • specifying objective and clear rules of functioning • existence of appeal procedures.

TWO POLES, THAT IS COST ANALYSIS OR PROJECTION The following are the most popular regulatory systems, widely described in literature and analyzed in many ways: • system based on rate of return on capital, the so called cost regulation • system based on setting a certain price level according to RPI – X [Retail Price Index) formula, called incentive regulation6. The cost regulation method comes from the USA, where the system of regulating private energy companies is based on many years of experience. The entrepreneurship culture in the United States is characterized by attachment to and recognition of private property and its protection. It is also reflected in the assumptions of the functioning regulatory system, with the key role of awarding the invested capital by a guarantee of return of the layouts made and the related rate of return, encouraging investors to continue operation and to develop it. It must be noted, however, that such guaranteeing the owner unquestioningly a certain rate of return on capital is not fully in agreement with the assumption of protecting the customers against unjustified level of prices adopted in most countries. In the situation when the owner has a guaranteed level of income (profit), he is not interested in increasing effectiveness of the company. The situation refers both to the company’s costs of operation (operational costs) and the level of investment layouts. In extreme cases, such a regulatory policy can lead to considerable over-investment and unnecessary, above-standard increase of service quality standard. Obviously, such a system does not offer any incentives for company cost reduction, thus for generating additional customer benefit in the form of services price decrease. Despite that, the profits of the given company do not exceed the permitted and approved by the regulator amount. It is a result of the guarantee of transferring of almost all costs of operation and lack of knowledge of the regulator on what their effective level is, he has limited possibilities of enforcing their reduction. Lack of knowledge on effectiveness levels of the companies of 6

Dobroczyńska A., Juchniewicz L., Zaleski B., op. cit. s. 26.

Sylwester Laskowski / ENERGA-OPERATOR S.A.

the sector may make the regulator have to face the problem of under-investment (due to too strict regulatory policy), thus lowering service quality standard and security of supply. This type of regulation actually comes down to detailed supervision over costs and profits of companies. In its analyses, cost regulation makes use of information on actual historical costs and requires its thorough verification by the regulator. By assumption, cost regulation provides for the company’s transfer of costs of operation, depreciation and return on the capital engaged into prices. If there occur external circumstances causing increase of costs of operation, the company can request increase of prices. Remembering about this disadvantage of cost regulation, consisting in lack of sufficient knowledge on effectiveness level, to force its improvement, the regulator makes sample controls that are to check whether certain investments were justified. But in such a case, he cannot fully influence investment processes of companies, because there is always the so called information asymmetry. The company will always be in a privileged position in terms of knowledge about its investment policy or operations. The regulator will never have the same knowledge about the company and its costs as the company management. Trying to force increased effectiveness, the regulator can make use of the so called regulatory delay, consisting in postponing decisions on price growth as long as possible. In such a situation the company, with the view of its financial standing deteriorating daily, will itself try to reduce costs of operation. One can risk a statement that cost regulation with the use of the mechanism of regulatory delay is a method finally leading to costs reduction and effectiveness improvement. One must remember, however, that when that mechanism is applied to effective companies, the effect can be different from the assumed one. The conditions of providing services can deteriorate, which may result in the necessity of introducing over-average increased price growth later on. Applying the method of regulatory delay requires great time and situation awareness on the part of the regulator, as the decisions made may cause real deterioration of condition of operation of companies. The other regulatory system, mentioned at the beginning of the chapter, that is incentive based regulation, was created as a result of the analysis of the cost method and is sometimes called a civilized form of regulatory delays. It is based on a system of incentives and penalties, which are to force regulated companies to behave in the ways expected by the regulator. The so called regulation and resignation from annual control of costs is the main element of the incentive based regulation in Poland. On the lapse of regulation period, of minimum 3–5 years, the so called regulation review is made. Based on that review, boundary conditions for the next regulation period are specified. Projections of costs, income, sales and supply of energy and power are subject for detailed control. After specifying boundary conditions, the regulator specifies the path of maximum growth (changes) in the next tariffs of the company (during regulation period). In specifying change pace, the boundary condition is the formula RPI – X, where RPI is the inflation rate (retail price index), and X is the assumed (expected) by the regulator improvement in the effectiveness of the functioning of the company. The formula is called a price-cap7. The company’s right to retain profits from improvement of effectiveness in individual periods between regulation reviews is the main advantage of this regulation. Lengthening the regulation period increases the company’s wish to improve effectiveness. Additionally, the company shares the benefits of improved effectiveness with the customers in the next regulation period, as there would not be any incentive from the regulator if all of the profits made were transferred to the customers. The company would not at all be interested in improving effectiveness of operation. It should be noted, however, that the method requires that the regulator should strictly control the quality standard, which could, theoretically speaking, become lower if the companies were very much determined to reduce costs of operation to make the projected profits, as energy companies can be inclined to postpone assets replacement investments. It can result in reduced safety and unreliability of the grid operation, which, due to the special character of energy sector, can have disastrous effects, posing a danger to the safety of citizens. The situation that took place in Great Britain in mid 19th century can be an example here. It was then that the competition between gas distribution companies – there were 14 of them in London alone – led to absurdly low costs of operation. Of course, they were reduced at the expense of the technical condition of the network infrastructures, which resulted in a considerable number of deaths due to gas poisoning. With that experience in mind, English authorities, later on followed by some other states, started to look closer at operation of natural monopolies and interfere in their activities. Municipal companies began to drive private companies from the market. From today’s perspective, we can say that those were the beginnings of the regulation of monopolies.

Regulation of Electrical Power Market

As mentioned before, in price-cap regulation method, following a regulation review, the regulator sets the level of income, the so called regulated income, for the first year of regulation. The rates for each following year, according to which the income will be indexed in the following years are also specified. Unlike in the methods of rate of return on capital, the company cannot increase prices freely when its costs of operation increase. Such a situation implies the necessity of undertaking by the company pro effectiveness activities to prevent negative effects of change of costs. Furthermore, due to adoption of the formula RPI – X and applying it to all entities, all the changes of external conditions of operation affect all the companies operating on the market. Another aspect in favour of this method consists in the fact that if during regulation period the company considerably improves its effectiveness and, as a consequence, reduces costs of operation below the level considered by the regulator to be justified, the company will be making excessive profits that in the entire regulation period will be retained by the owner. One can say that price-cap regulation rewards activities taken up to improve effectiveness. The amount of the so called regulated income is set based on justified operational costs, depreciation and return on capital, so in the same way as in the case of cost regulation. However, the methods differ considerably in the approach to the amount of operational costs. In price-cap method they do not include all operational costs, but just model justified costs, that is the ones that would be incurred by a hypothetical company operating in an effective way in the future. Justified costs are specified by the regulator, based on historical data and developed econometric models, bringing all the companies to one level, which enables comparing them. The significant elements of price-cap regulation include specifying the duration of regulation period, which significantly affects the company’s motivation to reduce costs and split the benefits between the customers and the owner. It is obvious that from the point of view of the company whose management can sees scope for activities to improve effectiveness, the longest regulation period is desirable because during that time the company will be able to benefit from improved effectiveness and at the same time - to postpone the time of sharing the benefits with the customers. In Polish regulatory system, the President of Energy Regulatory Office is responsible for, inter alia, specifying the duration of regulation period. The President of Energy Regulatory Office is also responsible for specifying: • corrective ratios, specifying the projected improvement of effectiveness of energy company functioning and change of conditions of performing certain type of operations by the company • tariffs and corrective ratios validity periods • amount of justified return on capital8. The main assumption of price-cap formula consists in reducing the costs – price dependence. One must remember, however, that too radical break up of those relations can lead to two extreme situations, that is: • when the financial standing of the owners deteriorates to such an extent that it leads to no investment • companies will make excessive, unjustified profits, based on which the regulator can be accused of lack of diligent protection of customer interests. Looking for optimal regulatory solutions leads to development of various methods in between the two, such as comparative regulation method, based on developing a system of measures and indicators that enable comparing various companies of the sector, and thus adequate specification of individualized parameters of improving effectiveness of their functioning9. Price regulation by comparing costs of companies that do not compete (lack of influence of the magic hand of the market) just imitates competition, because it not the customer that chooses a cheaper product (of the same quality) in a competitive market, but the company is given the price from the regulator. And as long as the company does not adapt its costs to the price given, it will not generate profits for its owner.

7 8 9

Dobroczyńska A., Juchniewicz L., Zaleski B., op. cit. s. 29. art. 23 item 2 p. 3 let. a), b) and c) of the Energy Law. Dobroczyńska A., Juchniewicz L., Zaleski B., opr. cit. p. 31.

Sylwester Laskowski / ENERGA-OPERATOR S.A.

LITERATURE 1. Directive 96/92/EC of European Parliament and the Council of 19 December 1996 concerning common rules for the internal market in electricity, OJ EC No L 27, 30/01/1997, pp. 20–29. 2. Directive 2003/54/EC concerning common rules for the internal market in electricity and repealing Directive 96/ 92/EC (OJ EC L 176 of 15.07.2003). 3. Ordinance of Minister of Economy of 4 May 2007 on detailed conditions of functioning of electrical power system, Journal of Laws, No 93, pos. 623 of 29 May 2007, with later amendments. 4. The Act on competition and consumer protection, Journal of Laws 2007, No 50, pos. 331, with later amendments. 5. The Act of 2 July 2004 on freedom of economic activity (Journal of Laws No 173, pos. 1807, with amendments). 6. The Act of 10 April 1997 – the Energy Law (Journal of Laws of 2006, No 89, pos. 625, with later amendments). 7. Baehr J., Stawicki E., Antczak J., The Energy Law. Commentary. Komentarz, Poznań 2001. 8. Baehr J., Stawicki E., Antczak J., The Energy Law. Commentary, Komentarz, Zakamycze 2003. 9. Dobroczyńska A., Juchniewicz L., Zaleski B., Regulacja energetyki w Polsce, Warszawa – Toruń 2001. 10. Publication edited by dr A. Dobroczyńska, Energetyka w Unii Europejskiej, Biblioteka Regulatora, Warszawa 2003.

rg nergetica.o e a t c .a w w w

Roman Partyka / Gdańsk University of Technology Daniel Kowalak / Gdańsk University of Technology

Authors / Biographies

Roman Partyka Gdańsk / Poland

Daniel Kowalak Gdańsk / Poland

Graduated from the Gdańsk University of Technology in 1972, receiving PhD in 1987 and DSc in electro-technology in 2007 at the alma mater. Employed at the Department of High Voltage and Electrical Apparatus. at the Gdańsk University of Technology. His scientiﬁc research is in the ﬁeld of electrical power with special focus on fault arc.

Graduated from the Faculty of Electrical and Control Engineering at the Gdańsk University of Technology in 2006. Currently employed there as an assistant. Areas of scientiﬁc interest: high voltage technology, plasma physics, arcing short-circuits and protection against their effects, electric arcs and design of electrical apparatus.

Dynamics of Fault Arc Traveling along Busbars in High Voltage Switchboards

DYNAMICS OF FAULT ARC TRAVELING ALONG BUSBARS IN HIGH VOLTAGE SWITCHBOARDS Roman Partyka / Gdańsk University of Technology Daniel Kowalak / Gdańsk University of Technology

1. INTRODUCTION In arcing short-circuits current electrodynamics cause the arc to move along busbar. The resulting rapid heating of the air inside the switchboard increases the pressure and may be hazardous for switchboard doors and covers. In enclosed, air-insulated switchboards the effect of arcing short-circuits depends on power of the arc and duration of the short-circuit. Thus, the thermal and electrodynamic impact of arcing short-circuits can be minimized most effectively by decreasing the short-circuit duration and limiting arc’s movement during its travel along busbars. 2. MAGNETIC INDUCTION AND ELECTRODYNAMIC FORCES BETWEEN BUSBARS In steady states (1) and magnetic induction (2) Where: H – vector of magnetic ﬁeld intensity J – vector of current density A – vector potential. The total force acting on the conductor element located inside the magnetic ﬁeld is expressed by the following relation: (3)

Abstract The paper presents the results of magnetic induction and electrodynamic force calculations acting on arc column during short-circuits in medium voltage air-insulated busbars. The gap between the bars was 120 mm and the anticipated short-circuit currents ranged from 4kA to 8kA. The paper also shows the measurement results of average velocity fault arc depending on currents and distance between bars. The relation between calculated arc diameter and arc current was established and described. Based on the calculation results of electrodynamic forces acting

on the arc and the calculated arc diameter, as well as the measurements of arc velocity, the relation of aerodynamic resistance coefﬁcient to arc current was presented. The conclusions indicate, inter alia, the possibility of changing arc’s traveling direction, as a result of changing the direction of electrodynamic forces Attention is also drawn to deformation of arc columns and increase in arc voltage, which cause increase in arc’s power, resulting in greater impact of tri-phase arcing short-circuits in switchboards.

Roman Partyka / Gdańsk University of Technology Daniel Kowalak / Gdańsk University of Technology

3. RESULTS OF INDUCTION AND FORCE CALCULATIONS The analysis was conducted on a copper ﬂat busbar arrangement of 40x5 mm and 40x10 mm cross-sectional dimensions and the in-between gap of 120 mm. The calculations took into account arcing short-circuits in the range 4 kA to 8 kA. Based on past research it was determined that during a tri-phase arcing short-circuit taking place on single plane bars there appear two active arcs – between the middle phase (bar) L2 and the external bars - L1 and L3 [2]. Through applying the relations (1), (2) and (3), calculations of induction (Fig. 1 and Fig. 2) and the forces acting on the arc during the short-circuit were obtained. The calculations were conducted using the software Flex PDE v. 5.1.2 [1]. Course of the resultant force acting on the arc column L1–L2 is presented in Fig. 3 and the relation of the average resultant Fyśr acting on the arc L1-L2 (placed perpendicularly to bar axis) to arc current IL is presented in Fig. 4. Assuming that at the moment of short-circuit’s occurrence the value of current in the phase L2 is equal to 0, after the time period of approximately 8ms the resultant force acting on the arc column L1-L2 is of minimum value and the arc is traveling towards the power supply side. There are two forces acting on the arc at the same time: from the currents of the bar L1 and the arc (force directed away from the power supply), as well as from the currents of the bar L2 and the arc L1-L2 (force directed towards the power supply). These co-acting forces cause deformation and signiﬁcant elongation of the arc (Fig. 2). This in turn increases the arc voltage. The arc deformation and the shifting of the arc footing increases the forces (of opposing directions) acting on the arc near the arc footing (Fig. 5, Curve 2).

Fig. 1. Component consistent with the axis direction from induction Bez [T] (z = 0) during a tri-phase arcing short-circuit – arc L1-L2 perpendicular to bar axis; t = app. 8 ms, arc current IL = 4 kA, bars 40x5 mm, resultant force Fy = – 0.82 N (directed towards supply source)

Dynamics of Fault Arc Traveling along Busbars in High Voltage Switchboards

Fig. 2. Component consistent with the axis direction from induction Bez [T] (z = 0) – arc L1-L2 shifted, t = app. 8 ms, resultant force Fy – 2.8 N, conditions as in Fig. 1

Fig. 3. Course of resultant force Fy acting on column L1-L2; arc current IL = 4 kA, bars 40x5 mm

Fig. 4. Relationship of average resultant force Fyśr acting on arc L1-L2 to arc current IL

1,6

1,2

0,8

0,4

Fig. 5. Relation of force per distance unit fy acting on the arc L1-L2 to distance x (from edge of bar L2 towards bar L1), 1 – arc as in Fig. 1, 2 – arc as in Fig.2, conditions as in Fig. 1

Fig. 6. Relation of measured average arc velocity vL along ﬂat arrangement tri-phase busbar to arc current IL and distance between bars d; 1 – d = 120 mm, 2 – d = 180 mm, 3 – d = 240 mm [2]

Roman Partyka / Gdańsk University of Technology Daniel Kowalak / Gdańsk University of Technology

4. ARC VELOCITY In analyzing the phenomena which accompany arcing short-circuits important role is played by the velocity of arc movement along bars. The velocity depends mainly on short-circuit currents and distances between bars. Analyzing the velocity is of particular importance in brief times of breaking short-circuits with traveling arc since with the same currents and distances between bars, the power and energy of arcing short-circuit is smaller in comparison with the power and energy of short-circuits with stationary arc. With the same currents and distances between bars, the voltage of a traveling arc is lower than that of a stationary arc [2]. Presented in Fig. 6 are the results of calculations of arc velocity vL, depending on short circuit currents IL with varied distances between bars [2]. Approximately linear relationship of arc vL to current IL was observed. There exist analytical methods allowing for calculating arc velocity. The following relationship may be used to define arc velocity: (4) Where: vL – arc velocity kFL – coefficient depending on short-circuit type cL – coefficient of arc’s aerodynamic resistance Fy – average electrodynamic force acting on arc, e.g., on column of arc L1-L2 AL. –cross-sectional area of column arc on a plane perpendicular to bar axis ρ – gas density The electrodynamic interaction force FL is proportional to the square of the IL, and the surface area AL grows with increase of the current IL. Calculations should take into account the aerodynamic resistance of gas inside the switchboard, placed on arc column moving along bars. Calculating the arc velocity vL based on the above relation (4) requires knowing the values of listed coefficients and measurements which are usually obtained by experiment. Cross-section area of column arc AL was set based on results of calculated arc diameter dL. According to literature [3] the dL diameter of arc cooled in gas environment is: (5) Where: p – gas pressure, MPa; assumed p = 0.1 MPa IL – arc current, A k = 0.4 × 10-2. m = 0.22÷0.27, n = 0.65 Relation of calculated arc diameter dL to arc current is presented in Figure 7. 1,64 1,6 1,56 1,52 1,48

Fig. 7. Relation of calculated arc diameter dL to arc current IL

Fig. 8. Relation of aerodynamic resistance coefﬁcient cL to arc current IL

Dynamics of Fault Arc Traveling along Busbars in High Voltage Switchboards

Using the results of average arc velocity measurements and the calculated arc column diameter, the analysis of change in arc’s aerodynamic resistance coefﬁcient cL was carried out with conversion of the relation (4). The relation of coefﬁcient cL to arc current IL is presented in Fig. 8. The calculation assumed kFL = 0.8 and gas density ρ20 = 1.18 kg/m3.

4. CONCLUSION Results of calculating magnetic induction and electrodynamic forces under the conditions of fault arc occurring in covered, air-insulated busbars allow for quite extensive analysis of velocity of arc movement along bars depending on arc parameters and busbar configurations. By using measurements results of average arc velocity in a flat busbar arrangement, one can calculate arc diameter, as well as coefficient of its aerodynamic resistance. The analysis presented above allows for forming the following conclusions: 1. During tri-phase arcing short-circuits occurring on bars placed on a single plane the traveling velocity of each of the two arcs (occurring between middle bar and outside ones) may differ due to the activity of electrodynamic forces of a tri-phase system. 2. Electrodynamic forces cause arc deformation and elongation, as well as rising arc voltage. This increases arc power and amplifies the effects of short-circuits in medium voltage switchboards. 3. Decreasing value of coefficient cL along with increasing value of current IL may point out to decreasing impact of the reversing arc phenomenon on the resultant arc velocity. The reversing arc phenomenon, i.e. changing direction of arc movement, stems from the activity of electrodynamic forces present in a tri-phase busbar arrangement. Detailed analysis of arc movement along bars allows for better assessment of the impact of arcing shortcircuits in switchboards and may contribute to significant reduction of negative effects, therefore improving the reliability and safety of using these switchboards.

LITERATURE 1. Flex PDE 5.1.2. User Guide. PDE Solution Inc. 2005. 2. Partyka R., Badanie skutków zwarć łukowych w rozdzielnicach osłoniętych, Monograﬁe 70, Politechnika Gdańska, Gdańsk 2006. 3. Ciok Z., Procesy łączeniowe w układach elektroenergetycznych, WNT Warszawa 1982.

Michał Porzeziński / Gdańsk University of Technology Grzegorz Redlarski / Gdańsk University of Technology

Authors / Biograﬁes

Michał Porzeziński Gdańsk / Polska

Grzegorz Redlarski Gdańsk / Poland

Assistant professor at the Faculty of Electrical and Control Engineering of the Gdansk University of Technology. He graduated from the University in 1992 and received a PhD in technical science in 2001. Main ﬁelds of interest include: microprocessor technology, building automation systems and computer control and supervision systems.

Assistant professor at the Faculty of Electrical and Control Engineering of the Gdansk University of Technology. He graduated from the University in 2000 and received a PhD in technical science in 2003. Areas of scientiﬁc research include, among others, reliability and efﬁciency of transmissions in computer networks and technical applications of computer systems.

Reliability of UDP Protocol Data Transmission in Electrical Power Telecomunication Systems Interworking with the Internet

RELIABILITY OF UDP PROTOCOL DATA TRANSMISSION IN ELECTRICAL POWER TELECOMUNICATION SYSTEMS INTERWORKING WITH THE INTERNET Michał Porzeziński / Technical University of Gdańsk Grzegorz Redlarski / Technical University of Gdańsk

1. INTRODUCTION Development of modern microprocessor technology and data processing systems witnessed in recent years is directly connected with the development of electrical telecommunication systems based on, among others, optical fibre technology. These new solutions find many practical applications in a variety of fields ranging from land-based and cellular telephony, through data transmission over LAN (Local Area Network) to transmission processes taking place in measuring devices and telemechanics. Thus they play a key role in controlling the work of electrical power systems, especially in the area of primary and secondary control, dispatch control and protection automation [3]. In addition, they are readily used in monitoring the condition of numerous systems and devices which constitute the structure of an electrical power system. There are two network areas within the structure of an electrical power teletransmission system: backbone SDH/ATM (Synchronous Digital Hierarchy/Asynchronous Transfer Mode) and access PDH (Plesiochronous Digital Hierarchy). Backbone network devices are installed in the most important locations, such as central company headquarters or power supply districts or, while access network devices are usually installed in electrical power stations and alerting posts Physical double-ring typology of the B-SHR type is used .within the range of SDH/ATM networks. In this solution physical connections are carried out through parallel fibre optic lines built into OPGWs (Optical Ground Wire). Within such physical typology numerous technologies (e.g. STM-1, STM-4, STM-16) and standards (e.g. V.24, V.35, G.703) are employed allowing for communication of various transmission parameters. Various physical typologies are employed within PDH networks (e.g. bus. star, mesh, ring), as well as logical typologies (e.g. broadcasting, token passing), which are jointly responsible for continuity and reliability of communication processes [1, 2, 3]. Teleinformatic infrastructure of an electrical power system and continuous development of modern technologies, as well as the trend to increase reliability of electrical power systems result in a search for increasingly more effective solutions. Research activities conducted in numerous centres concentrate on a number of important processes which take place in electrical power systems. Without a doubt, one of them is the process of automatic synchronization which when incorrect may have many serious negative consequences of legal, social and financial nature. Improving the reliability of this process may be achieved through, among others, improving the reliability of devices carrying out synchronization functions such as UASP automatic generator synchronizers. Despite the fact that modern UASP are high-class microprocessor devices, various types of breakdowns still occur. Diagnostic processes usually are restricted to the so called periodic maintenance. Therefore, it is not possible to constantly monitor their current conduction which would be possible after equipping the UASP

Abstract The paper presents the principle of reliability in data transmission based on the UDP transmission protocol model without implicit hand-shaking dialogues in electrical power transmission systems interworking with the Internet. The subject matter applies especially to small (frequently maintenance free) electrical power objects in which the monitoring process may be conducted through the widely available infrastructure of the Internet and a

monitoring centre. The paper points out the most signiﬁcant sources of errors in the transmission process and indicates possibilities of their elimination. In addition, the work presents developed diagnostic tools, methodology, as well as results of conducted research and its most signiﬁcant conclusions.

Michał Porzeziński / Gdańsk University of Technology Grzegorz Redlarski / Gdańsk University of Technology

devices with appropriate diagnostic software and sometimes also interfaces allowing them to work together with a computer network. This in turn would allow for the information on device condition to be transferred directly to application located in, for example, the monitoring centre. However, such steps require research and implementation, among others, in the area of the method of information transfer between examined device .and applications with access to the Internet. Without a doubt, one of the basic issues which needs to be answered is the choice of communication protocol and the effectiveness of its function. In practice, a number of communication protocols may be employed for data transmission. Due to their popularity, two of them deserve special attention [5, 6]: TCP (Transmission Control Protocol) whose format is presented in Fig. 1 and UDP (User Datagram Protocol) with format presented in Fig. 2. Source Port

Destination Port

Sequence Number

Acknowledgement Number

HLEN

Reserved

Window

Checksum

Urgent pointer

Options

Padding

Data...

Control Bits

Fig. 1. TCP protocol segment format

Source Address

Destination Address

UDP Lenght

Checksum

Data...

Fig. 2. UDP protocol segment format

Definitions of segment fields in Fig. 1 and Fig. 2 [1,5,6]: • Source Port – specifies the calling port, which may be connection initiating point • Destination Port – specifies the destination port number • Sequence Number– specifies the sequence order within data chain transmitted to receiver • Acknowledgement Number– specifies the number of the next expected octet of data • HLEN – specifies the number of 32-bite words appearing in data segment • Reserved – field with entered ‘0’ value • Control Bits – field of control functions (e.g. relevant to the way of configuring and ending given session) • Window – field determining the size of sliding window (in bites) which may be accepted by device • UDP Length – specifies the length of data field in case of UDP protocol • Checksum – determines the correctness of data transmission, based on a defined working algorithm and the information contained in the header and data fields • Urgent Pointer – specifies the completion point of important data transfer • Options – allows for defining the maximum size of TCP segment • Data – field of the actual data sent with TCP or UDP protocols. TCP protocol is characterised by the fact that prior to initiating the transmission process, a connection with the target device is established as part of the process known as the three-way-handshake [1]. In addition, it contains mechanisms ensuring reliability of data transmission, such as sequence numbers, confirmation numbers and sliding windows. In contrast, the UDP protocol does not establish connections with target device prior to beginning the transmission process and is not equipped with mechanism ensuring reliability. Therefore, without implicit handshaking dialogues in the UDP protocol, it is necessary to ensure sufficient transmission reliability level at the application layer level. However, in order to make sure that the mechanism is effective and efficient it is first necessary to assess the probability of transmission errors and their character. In practice, one can frequently encounter situations where the Internet is employed in monitoring the condition of devices in distributed objects of low power-rating. In addition, due to the high cost of establishing and maintaining a separate network it seems justifiable to use the Internet for communication in certain situations (e.g. where the reliability of data transmission in real time is not critically important). Therefore, if one takes into account the efficient, ‘enclosed’ and so highly reliable structure of electrical power teletransmission

Reliability of UDP Protocol Data Transmission in Electrical Power Telecomunication Systems Interworking with the Internet

network, as well as the necessity of data transmission between that network and the monitoring centre through the widely accessible connections of the Internet (Fig. 3), it is very important to conduct the Internet network reliability research, especially if it is not a familiar transmission path or if diverse interference causing factors may appear. Monitoring Center

Wide Area Network in Power Electric System Internet

Fig. 3. General schematic presenting interworking between teleinformatic WAN network of electrical power system and the Internet

SOURCES OF UDP TRANSMISSION ERRORS AND CAUSES OF THEIR FORMATION Potential errors causing UDP protocol data loss are mostly connected with random faults which usually occur at the physical surface level of computer network and with errors of devices serving higher protocol layers. On the level of physical network layer especially important role is played by the EMI and RFI type interferences, incorrect functioning of devices within a given network which are often the result of badly designed physical network typology, mechanical damage of transmission pathways, as well as factors causing power supply failures. There are many possible causes of incorrect design of physical typology. Considered to be among the most important ones are the following: exceeding allowed parameters of employed transmission media (e.g. cable length), inaccurate completion of cable connections (e.g. excessive value of transfer impedance), insufficient width of transmission band, or employing network devices unfit for requirements. These factors may constitute the causes of, among others, increased amount of collisions, possibly leading to not only decreased network efficiency but also to increase in the amount of lost data transmitted through the UDP protocol [1, 2]. Defective network devices which cause loss of transmission are frequently connected with interface and power supply malfunctions. In such cases, restoring network convergence requires a defined period of time necessary for, among others, finding another (functional) transmission path. In addition, loss of IP packets in network devices, such as switches and routers, may be the result of excessive loads caused by large amount of data transmitted in a short period of time and its related overfilling of internal buffers.

Michał Porzeziński / Gdańsk University of Technology Grzegorz Redlarski / Gdańsk University of Technology

1. NETWORK MONITORING TOOLS Researching the reliability of UPD protocol based data transmission requires development of software for recording selected transmission parameters based on which a given transmission channel can be evaluated. Fig. 4 presents a window view from TestUdp - an example of software developed for such a purpose.

Fig. 4. Window of a network monitoring software programme

The software programme presented above was prepared in two versions. The first version allows for sending of consecutive segments with a 10 second time interval. In the second version three segments containing the same information are sent after the same pause (with user defined pause duration). The software has to be run in the diagnostic points between which the data transmission process is taking place. One of the applications (Station A) plays the sending (local) host1 role while the other (Station B) plays the role of receiving host (remote) which sends the received data back to the sender. Configuring the software requires providing IP address of the remote host and defining numbers of the ports to be used in the transmission process. The quantity of sent and received UDP segments is visualised in a continuous way in the fields Send and Receive or , RcvCnt and RetCnt (depending on software version). Detailed information on the obtained research results, i.e. transmission time, number of data segments, transmission delay, as well as information on successful or unsuccessful transmission attempt are collected in a text file acting as event log.

1. RELIABILITY ANALYSIS OF UDP TRANSMISSION IN THE INTERNET Investigation was limited to a few nodal points between which the process of UDP protocol data exchange was established for various time periods. The research range was divided into two stages. In the ﬁrst transmission reliability was examined based on the ﬁrst software version. Single data transmission after which the sent segment reached its destination was regarded as the correct condition. The study results obtained for the connections indicated in Fig. 5 with the symbols P-P 1 to P-P 7 are presented in Table 1.

1 etc.

In the terminology of computer networks, the term host refers to devices with a MAC address, i.e. personal computers, terminals, servers

Reliability of UDP Protocol Data Transmission in Electrical Power Telecomunication Systems Interworking with the Internet

Fig. 5. Map of connections carried out during the study

Table 1. Results of reliability analysis of UDP protocol based data transmission Connection No. (Fig. 5)

Connection duraNumber Amount of of errors tion data [hh:mm:ss] (1/2/3/4/5)*

Number of errors [%]

Average delay [ms]

Maximum delay [ms]

Minimum delay[ms]

Node information

P-P 1

23:32:10

8474

10 (5/0/0/0/1)

0.12

0.056

Academic network – Academic network

P-P 2

10:46:31

3817

38 (38/0/0/0/0)

0.99

2.003

4641

Academic network – Cable TV network

P-P 3

07:08:40

2597

11 (3/0/1/0/1)

0.42

186. 49

1829

Neostrada TP – Neostrada TP

P-P 4

06:38:16

1969

148 (118/12/2/ 0/0)

7.52

200.67

1 482

WiFi network – Neostrada TP

P-P 5

02:07:31

766

1 (1/0/0/0/0)

0.13

38.56

250

Academic network – Neostrada TP

P-P 6

50:17:31

18106

149 1.16 (142/2/1/0/0)

0.0612

Academic network – Neostrada TP

P-P 7

26:03:23

9374

54 (54/0/0/0/0)

52.84

3650

WiFi network – Neostrada TP

0.58

* Number of errors occurring in succession: single/double/triple…

Based on the analysis of study ﬁndings presented in Table 1, it may be concluded that they are of a random character depending on the degree of transmission delay and the number of lost UDP segments. In addition, in all completed transmission processes there appears a variable amount of lost UDP data, which without a doubt depends on the current condition of transmission links. . In various transmissions links there also appear different delay values in transmission processes. Additional research which took the above factors into account was done to examine the relation between the degree of delay and the number of faulty data segments, the impact on transmission quality of additionally

Michał Porzeziński / Gdańsk University of Technology Grzegorz Redlarski / Gdańsk University of Technology

delay [ms]

placed transmission sessions containing identical data segments, as well as the effect of redundancy based on multiplying the number of sent signals contain the same information on the quality of transmission. The ﬁrst of the discussed aspect was addressed to the transmission process marked in Fig. 5 with the symbol P-P 8. The obtained results are presented in Fig. 6.

Fig. 6. 24-hour characteristic of transmission delay times and lost UDP data in a selected link in the Internet

Time of the day

Based on information from Fig.6 it can be concluded that in the hours of heightened connection activity (working hours and evening) there appear the largest delays in transmission processes. In addition, during the working hours (7:12–16:48) there is a signiﬁcantly lower degree of data loss (15 segments) than outside those hours (37 segments). Analysis of the results also points out that the majority of the errors were single ones which were most probably connected with accidental data loss. However, one should also bear in mind the possibility of longer breaks in the functioning of transmission channels ranging from several seconds to a minute or even minutes. Researching the impact of extra channels on transmission quality (constituting of establishing additional sessions for sending the same data segments) was limited to the connection sample P-P 8. The study ﬁndings for N 3Ni = 1, 2, 3, 4 redundancy paths are presented in Table 2 ( C N2Ni and CN represent the biggest number of errors in series: two out of four established transmission paths and three out of four established transmission paths). Table 2. Impact of channel redundancy on the quality of UDP transmission process Maximum number of transmission errors Amount of data

18106

N1 ∨ N2 ∨ N3 ∨ N4 149

N1 ∧ N2 ∧ N3 ∧ N4 20

C N2Ni

3Ni

6 CN

Max. transmission delay [ms] 94

Due to the observed random character of transmission errors (see Table 2), it can be concluded that establishing redundant transmission channels, as well as repeating the information at appropriately selected time intervals is an effective method of improving the reli ability of UDP transmission. The strongest impact occurs after employing just a single additional transmission channel. In such a case, the number of transmission errors decreases nearly by an order of magnitude (out of the observed 149 for a single channel to 20 for the scenario with one additional channel). Examining the impact of redundancy based on multiplying the sent amount of data containing the same information was limited to the connection sample P-P 8. The software version based on sending three data segments in each transmission cycle was employed in this case. The three segments contain the same information and the assumption is that correct transmission takes place if at least one of the segments reaches its destination. The pause between successive sent packets is defined by the operator in the field entitled ‘Pause’, while the time period between successive packets containing the information is set in the field „Sending” (see Fig.4). Results of the conducted study are presented in Table 3.

Reliability of UDP Protocol Data Transmission in Electrical Power Telecomunication Systems Interworking with the Internet

Table 3. Impact of redundancy of sent segments on the quality of UDP transmission process Software settings and study results Sending / Pause

10 s / 10 ms

10 s / 3 s

60 s / 10 ms

60 s / 3 s

Amount of data

8655

8644

1438

1436

Number of errors

182

Number of transmission pauses

Covering coefﬁcient

Full

After analyzing the data from Table 3, it can be concluded that separating redundant data segments in time has a positive impact on the reliability of the transmission process. In both of the examined transmissions, i.e. for the sending times of 10 and 60 seconds and the pauses of 10 ms and 3 s respectively, the number of lost data segments is smaller when the pauses are longer and amount to 3s. This is caused by the fact that interferences in the transmission channel are as a rule of short duration, which means that if the channel remains nonactive for a sufﬁciently long period of time, then despite the sending of three segments containing the same data at 10 ms time intervals, they are not going to reach their destination. Furthermore, a more detailed analysis of the data collected in programme logs, allows us to observe that longer pauses of transmission channel inactivity appear in the same way in all the programme logs and increasing the pause between redundant data signals can not change anything. The degree to which such a situation may appear is indicated by the parameter ‘Covering coefﬁcient” (see Table 3). In the discussed case, long duration of channel inactivity was recorded in all the programme logs and lasted about 13 minutes.

CONCLUSION The dynamically developing infrastructure of the Internet working together with the WAN teletransmission network functioning in electrical power system may constitute the foundation for constructing inexpensive systems for monitoring objects distributed over a large geographic area [4]. The research work carried out by the authors indicates that: • quality of data transmission based on the standard UDP protocol in the examined networks is sufﬁcient for executing monitoring and diagnostic tasks in which the required reaction time is measured in the range of minutes or even hours • due to the possibility of the occurrence of random transmission errors it is appropriate to employ additional methods which effectively improve the reliability of transmission processes, for example, establishing redundant transmission channels and sending extra data segments containing the same set of information at appropriately selected time intervals • protecting data and system against sabotage by other users of the network is a separate issue which requiring further research.

LITERATURE 1. Cisco Networking Academy program, CCNA 1 and 2 Companion Guide, 3rd Edition. Cisco Systems Inc., 2004. 2. Cisco Networking Academy program CCNA 3 and 4 Companion Guide, 3rd Edition. Cisco Systems Inc., 2004. 3. Poradnik inżyniera elektryka, v. III, chapter 7, Editor in chief Prof. Zbigniew Szczerba. Wydawnictwa Naukowo-Techniczne, Warszawa, 2005. 4. Porzeziński M., Mazur L., Remote monitoring and control of technical systems using internet network technology, Proceedings of the IEEE International Conference on Technologies for Homeland Security and Safety TEHOSS, Gdańsk 2005. 5. http://www.ietf.org/rfc/rfc0768.txt (March 2009). 6. http://www.ietf.org/rfc/rfc0793.txt (March 2009).

Zbigniew Szczerba / Gdańsk University of Technology

Authors / Biographies

Zbigniew Szczerba Gdańsk / Poland Zbigniew Szczerba was awarded the diploma of an engineer in 1952. Four years later he was awarded master’s degree in technical sciences, and in 1963 – the degree of a doctor of technical sciences at the Faculty of Electrical Engineering of Gdańsk University of Technology. In the Institute of Power Engineering he headed, inter alia, his team that developed many types of excitation systems and voltage regulators of generators of the voltage from a few tens of kW, for shipbuilding – up to 500 MW. There was a time when the generators controlled by those regulators made up 75% of the power of the national electrical power system. In 1972 Zbigniew Szczerba was transferred to the Institute of Power Systems Automation in Wrocław and appointed a deputy head for scientiﬁc research. In 1977 he was awarded the degree of habilitated doctor. He became the head of the Chair of Electrical Power Engineering at the Faculty of Electrical Engineering of Gdańsk University of Technology. Soon afterwards he became a professor, and was twice elected the dean of the faculty. In the period of 1987–90 he worked as a visiting-professor at Technical University in Oran (Algeria). On his return to Poland he organized a Chair of Electrical Power Systems at the present Faculty of Electrotechnics and Automation. He has been a full professor of Gdańsk University of Technology since 1991. In the period of 1990–1996 he was the pro-rector for scientiﬁc research. He is an author or co-author of over 50 patents, of over 200 research papers. Most of his ideas have found practical applications.

Should kvarh Meters be Used?

SHOULD k varh METERS BE USED? Zbigniew Szczerba / Gdańsk University of Technology

Distribution companies charge for supply of reactive power and energy only in relations with big consumers. The charges – dependent on reactive energy consumed and on average tgϕ during the month – are incorrect from the point of view of justiﬁcation of costs incurred by the supplier. Firstly: they do not include ﬁxed costs Ks = f (QM). Where QM – maximum value of reactive power consumed. Secondly:

, called “reactive energy”, is treated in the same way as active energy.

In the charge for supply of active energy, variable costs in the given time zone are, in rough approximation, proportional to costs of fuel. Integration in time is thus fully justiﬁed. In the case of costs connected with supply, variable in time and reactive power, variable costs result mainly from costs of losses. Active power losses caused by supply of reactive power, that is costs, are not at all proportional to the supplied reactive power. If active power losses are caused by supply of reactive power to only one big consumer, then active power losses are proportional to the square of reactive component of current (not to the square of reactive power) and are not at all proportional to the reactive power consumed. Cost in the given time T thus depends on And not on

, called “reactive energy” hereinafter (in kvarh).

Theoretically, from the point of view costs, relating charges to indications of kvarh meters has so basic, cardinal errors that it cannot be justiﬁed at all. Charges connected with indications of those meters have, however, a disciplinary impact on consumers in terms of avoiding reactive power consumption/demand. If a consumer (2) is connected to the line of another, much bigger consumer (1) – losses in feeding line, caused by ﬂow of reactive power, will be proportional do the square of the reactive components of the current of both consumers. When the method similar to calculation of marginal costs is used, losses increase is: Losses caused by increase of line load, induced by reactive power consumption by another consumer, depend not only the square of reactive component of the current consumed by this consumer, but also on the product of reactive components of the currents of both consumers. The integral of the sum of these dependences (varied in time in a different way) is not in any way related to the integral of reactive power in time, usually called “reactive energy” calculated by kvarh meter. If the method of marginal costs is rejected and the costs are divided pro rata (according to an arbitrarily assumed way) between both consumers, then also in this case variable costs will depend on the integral of the

Abstract Supply and consumption of reactive power are charged and settled based on readings of kvarh meters. The article demonstrates, on examples, that indications of those meters do not have any connection with the costs of supply and consumption of reactive power. It shows that the currently available measurement technology enables using new generation meters of operation algorithms relating indications to justiﬁed costs.

Zbigniew Szczerba / Gdańsk University of Technology

square of the sum of reactive components of the currents of both consumers, and not on the sum of the integrals in time, of the reactive power consumed by them. Moreover, the measurements of “reactive energy” measured by kvarh meter do not take into account the fact that variable costs (caused by losses) are inversely proportional to the square of voltage, and not to the product of voltage and reactive component of the current. By increasing the voltage (within permitted limits) the supplier of reactive power decreases his variable costs, and the meter still integrates the product U × IQ. The present way of settlement tries to compensate these disadvantages by introducing a threshold depending on average tgϕ during a month and progression of price depending on the value of that tgϕ. Example Two simple types of power consumption by two consumers from a line where there are losses are compared. In both cases the indications of kvarh meters are the same: A. Consumption of reactive power presented in Fig. 1. B. Consumption of reactive power presented in Fig. 2.

Fig. 1. Case A, Q(t)

Fig. 2. Case B, Q(t)

In both power consumptions kvarh meters indications after time T – will be the same:

In consumer A, energy of losses: and in consumer B: Also fixed costs, in the case of installing a capacitor unit, proportionally to maximum reactive power, will be: In consumer A: C × QM = 0,1C, and in consumer B: C × QM = 1C The example proves that the quantitative indications of kvarh meters have no connected with fixed costs or with variable costs of reactive power supplied. As follows from the above considerations, the cost of supply of reactive power in a given time section does not have anything to do with the supply of active power. Making charges thresholds dependent on average tgϕ does not have any justification in costs, despite the fact that it is justified by forcing consumers to reduce consumption of reactive power. The above considerations prove that indications of reactive energy (kvarh) meters, usually used for settlements for supply of reactive power variable in time, are not in any way theoretically justified. They do not provide information on fixed costs and provide false information on variable costs.

Should kvarh Meters be Used?

Using kvarh meters is a result of getting accustomed to the existing state of affairs and the routine, resulting probably from a false analogy to the energy measured by kWh meters. Kvarh meters probably started to be used at the beginning of 20th century because of the above mentioned analogy to active energy meters, but due to construction difﬁculties, resulting from the technology available at that time, no meters more rationally rendering the relations cost – price were developed.

CONCLUSION The current level of measurement technology enables a radical change of the way of measuring this system service for settlement purposes. The settlement should be based on two components: • Measurement of maximum reactive power in the settlement period • Component – price.

(or one similar to it) describing more correctly than

the relation cost

• Measurement of maximum reactive power in the settlement period will enable including ﬁxed costs in justiﬁed charges, and the measurement of costs.

(or a similar component) - including justiﬁed variable

The technologies available nowadays enable development and supply of adequate measurement devices of new generation – meters of the services connected with reactive power – at the price enabling its general use. Replacing kvarh meters with the proposed measurement devices does not pose any construction or application difﬁculties. Many Polish companies are able to develop and offer them soon. The operator of the transmission system and electrical power companies should develop and implement of measuring the “reactive power” system service adequate to 21st century technology. The article presents a signiﬁcant problem that needs to be solved at the time of modernizing market mechanisms in the power sector.

LITERATURE Szczerba Z., Czy pomiar „mocy biernej” ma sens?, Zeszyty Naukowe Politechniki Gdańskiej 2000.

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

Authors / Biographies

Aleksander Kot Kraków / Poland

Waldemar L. Szpyra Kraków / Poland

Graduated from the Faculty of Electrical Engineering, Automatics, IT and Electronics with the diploma of MSc. Engineer. (1997). He was awarded the degree of doctor in the same faculty (2005). Now he is employed as an assistant professor in the Chair of Electrical Engineering and Electrical Power of AGH University of Science and Technology. His professional interests focus on: analysis and estimation of operation condition of distribution networks, problems of optimization for the purposes of designing and operation, artiﬁcial intelligence, forecasting and planning of network development, IT systems in electrical power industry, energy market.

He obtained the diploma of engineer electrician in the Faculty of Electrical Engineering of AGH University of Science and Technology in Kraków in 1975, and PhD – in the Faculty of Electrical Engineering, Automatics, IT and Electronics of AGH University of Science and Technology in Kraków in 1998. Now - an assistant professor in the Chair of Electrical Engineering and Electrical Power Engineering of his University. He is involved in modelling, work status estimation and optimization of distribution networks, application of artiﬁcial intelligence methods in electrical power engineering and electrical power management.

Optimal Voltage Control in Medium Voltage Power Engineering Networks

OPTIMAL VOLTAGE CONTROL IN MEDIUM VOLTAGE POWER DISTRIBUTION NETWORKS Waldemar Szpyra / AGH University of Science and Technology in Cracow Aleksander Kot / AGH University of Science and Technology in Cracow

1. VOLTAGE DEVIATIONS LIMITATIONS Limitations for voltage deviations in power distribution networks are given in the Ordinance of the Minister of Economy dated May 4, 2007 on specific conditions of electric power systems. (Journal of Laws no 93 dated 29 May 2007, item 623) [17], called in short “system regulation”. The Ordinance imposes a duty on power line operators to observe specified quality parameters of supplied power. It stipulates that in a network operating without disturbance, every week 95% out of a set of 10 minute average values of effective input voltage should remain within the following deviation range: • for consumers classified as group I and II connected to a grid:of nominal voltage: Un = 400 kV: +5% /–10%Un Un = 220 i Un = 110 kV: ±10%Un • for consumers classified as group III ÷ V (supplied with network of nominal voltage below 110 kV) – every week 95% out of a set of 10 minute average values of effective input voltage should be in the deviation range ±10% rated voltage. For consumers of group I and II – power quality parameters may, in their entirety or in part, be substituted by other parameters specified in the power sales contract or in a contract for rendering power transmission and distribution services. Failure to observe quality standards of supplied power to consumers from group III, IV and V specified in the system regulations [17], entitles consumers to bonuses and discounts. The discount values are determined according to §37 of the Ordinance of the Minister of Economy dated 2 July 2007 on specific principles governing the calculation tariffs and financial settlements in electric power trading (Journal of laws dated 18 July 2007, no 128, item 895) [16]. Both Ordinances were issued on the grounds of delegation stipulated in the Act on Energy Law [21]. The Acts referred to above do not define the term “grids operating without disturbance”. “Instructions of Transmission System Operation and Maintenance” [4], on the other hand, define disturbance as: “Unplanned automatic or manual shut-down(s) or impossibility to keeping of the expected operating parameters of the components of network assets. The disturbance can take place with or without the damage to the network assets”. A conclusion may be drawn from the definition that energy quality parameters need not be met in systems other than typical/normal systems. Thus, the regulations related to voltage in distribution networks in force today are more liberalised as compared to those binding before the system regulation of May 2007 became effective (regulations on operations of power engineering systems issued before 2007 did not stipulate any restrictions as to “networks operating without disturbance”. Abstract Power flow in elements of the network causes voltage drops in these elements. Therefore, in order to ensure the proper voltage of electric power delivered to consumers it is necessary to regulate voltage in power engineering grids. The article presents voltage requirements in power engineering grids, the impact of regulation on losses in distribution lines and various criteria for optimising voltage regulation. Depending on the adopted criteria, indications for tapping switch settings in transformers and input voltage may differ for various lines or even be quite the opposite.

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Scie nce and Technology in Cracow

2. DEVIATION AND VOLTAGE DROP BALANCE

The deliberations refer to a MV network supplied by a HV/MV transformer installed in a power distribution substation (DS). A single transformer feeds 6 ÷ 10 medium voltage lines. Each line feeds several to few dozen medium voltage/low voltage (MV/LV) transformer stations, which supply low voltage circuits. An example of the supply system from distribution substation to the consumer connected in point k of the low voltage network with marked deviations and voltage drops is given in Fig. 1.

LV line

LV line Customer load

Customer load

Fig. 1. Deviations and voltage drops in the system from distribution substation to the consumer connected in point k to the low voltage system. Key: R – point of network split; TS - MV/LV transformer station; other designations in text

In the case given in Fig. 1 the voltage deviations δU in point k of the low voltage system may be determined from the deviations and voltage drop datasheet expressed in the following equation: (1) where: δUnn – is the voltage drop in the low voltage system from the TS to point k; ΔUT – drop in voltage in the MV/LV transformer; δUzT – voltage deviation resulting from the position of the tap changer to medium/ low voltage transformer ratio control; ΔUSN – voltage drop in medium voltage network; δUz – deviation voltage in network supply point; Unn – rated voltage of low voltage lines; δUϑ – voltage deviation resulting from the difference between the relations of the transformer rated voltage and the network rated voltage: (2) where: ϑnT – rated MV/LV transformation ratio; ϑnS – the relation of medium network and low network rated voltages; UnG – rated voltage of the MV winding of MV/LV transformer, UnD – rated voltage of the LV winding of MV/LV transformer, USN – rated voltage of MV networks, Unn – rated voltage of LV networks,. Voltage deviation in any point of medium and low voltage system must comply with the range given in the system regulation, i.e. (3) In a normally operating system the maximum voltage deviations occurs in the end of the low voltage line supplied by the most loaded TS distanced from the grid feeding medium voltsage network (usually close to the point of network split). Minimum voltage deviations occur in the case of minimum network load at the beginning the low voltage system, fed by the TS located near DS. To assess the voltage in distribution networks it is necessary to know all the elements of the deviation and voltage drop datasheet (1). Usually a model, reﬂecting precisely the network parameters from the grid feeding

Optimal Voltage Control in Medium Voltage Power Engineering Networks

MV network to low voltage busbars in TS, is built to analyze a distribution network. Precise models of low voltage networks are not developed. This results from the big number and diversification of low voltage circuits in the system. In practice calculations are made of the power current flow and voltage drop in the MHV network to assess the network operating conditions. Therefore, it is justified to specify the voltage drop limits, i.e. values that allow for the present voltage adjustment system to maintain the deviation level for the consumer within the admissible range. Specifying the admissible voltage drop in the MHV network is possible provided values of certain datasheet components are adopted (1). The most often made assumptions involve: • use of the full admissible voltage range on MV bus bars is possible in the network feeding point, which means that deviation of input voltage δUz may read +10%Un (control practice used by power distributers often restricts the supply voltage deviation in the MHV network in GPZ to δUz = +5%Un – primarily because bigger customers belonging to group III have their own MHV/LV transformer stations) • voltage deviation resulting from the difference between the relations of the transformer rated voltage and the network rated voltage (δUϑ) shall be compensated by relevant setting of tap changer (δUzT) • a voltage drop in the MV/LV transformer (ΔUT) is calculated using the average known transformer load in the circuit and its rated parameters • low voltage networks are designed according to guidelines given in [22] and thus we can assume that voltage drops occurring in these systems (ΔUnn) do not exceed the values given in the last column of Table 1. Table 1. Admissible voltage drops in medium and low voltage lines according to guidelines given in [22] Specification

MV network

Low voltage network

normal

disturbed

Towns supplied by 110 kV/MHV lines located within town borders

4.5%

Towns supplied by MFP located within town borders

10%

(3÷4.5)%

Towns supplied by distanced MFP

13%

(7.5÷10)%

Industrial consumers Supplied from regional grid

13%

(3÷4.5)%

Voltage drop in a MV/LV transformer may be calculated according to the following formulae: (4) where: SN – transformer rated power [kVA]; S – transformer load [kVA]; cosφ – transformer load coefﬁcient (ratio of active to complex transformer demand); ur – active component of transformer’s short-circuit voltage [%]; ux – reactive component of transformer’s short-circuit voltage [%]; (5)

(6)

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

where: Pk – load loss of transformer (cooper losses) [kW]; uk – transformer short circuit voltage [%]. Table 2 presents the voltage drop value for typical MV/LV transformers used in distribution systems in the load function S/SN, and load coefﬁcient of cosφ = 0.9. Table 2. 15.75/0.4 kV transformer voltage drop under varied load Sn

Transformer load factor S/Sn 0.3

0.4

0.5

0.6

0.7

0.8

0.9

Voltage drop in transformer ΔUT [%]

kVA

[%]

1.20

4.5

1.19

1.59

1.99

2.39

2.79

3.19

3.59

1.85

4.5

1.24

1.65

2.06

2.48

2.89

3.31

3.72

100

1.75

4.5

1.19

1.59

1.98

2.38

2.78

3.18

3.58

160

2.25

4.5

1.05

1.41

1.76

2.11

2.47

2.82

3.18

200

3.90

4.5

0.94

1.26

1.57

1.89

2.20

2.52

2.84

250

3.00

4.5

0.99

1.33

1.66

1.99

2.33

2.66

3.00

400

4.25

4.5

0.91

1.21

1.51

1.82

2.12

2.43

2.74

630

6.10

1.09

1.46

1.83

2.20

2.58

2.95

3.32

The average peak transformer load in distribution networks reaches 40÷50% of rated power, which means that the average voltage drop in transformers should not exceed 2%. Assuming that: δUz = +10%; δUϑ = –5%; δUzT = +5%; ΔUT = –2%; ΔUnn = 10% and admissible voltage deviation for consumers supplied from low voltage networks, amounting to δUdop = 10%, the voltage drop and deviations (1) show that the maximum voltage drop in MV lines should not exceed:

= 10 – 5 + 5 – 2.5 – 10+10 = 7.5 [%] This means that full range voltage regulations in DS allow for assuring the required low voltage level at the consumer’s end (voltage drop in MV network amounting to circa 7.5%).

3. VOLTAGE REGULATION MEANS Voltage deviation in low voltage networks can be controlled: 1. without investment outlays – using transformer’s regulation capacity, i.e.: a. change of input voltage to the MV network – regulating voltage on MV busbars in DS – by changing the HV/MV transformation ratio operating under load, by ±10% in 8 steps or ±16% in 12 steps b. change of MV/LV transformer ratio control while the transformer is switch-off),– the extent of change depends on the transformer’s year of built and reaches: δUzT = {-5%, 0%, +5%} or δUzT = {–2,5%, 0%, +2,5%, +5%, +7,5%}. 2. investment related – applying additional technical means to reduce the drop in network voltage, i.e.: c. installing condenser batteries to compensate reactive power d. installing condenser’s in series to compensate line reactance e. installing controlling auto transformers in series (buck transformers) f. connecting new circuits to DS taking over delivery to some of the TS g. shortening low voltage circuits by adding new TS. Voltage control options, resulting from application of means mentioned above, are limited because: a. higher input voltage to the medium voltage network is limited by the maximum voltage upward deviations limited by inequality (3), and sometimes by contract conditions with consumers

Optimal Voltage Control in Medium Voltage Power Engineering Networks

b. MV/LV transformation ratio is connected with consumer trip off and results in generating costs of the rigging team and is in practice rarely applied (once or twice a year or even less often). Additionally, the increase of rated voltage in low voltage networks in 2003 resulted in growing maladjustment of transformer ratio control and relation of rated voltage in medium and low voltage networks – the value of δUϑ was modiﬁed from +0,25% to –5% and as effect up to 5% of the medium/ low voltage transformer regulation range is used for compensating the effects of increased voltage in the low voltage network c. application of additional technical means to reduce voltage drop requires considerable investment outlays, which in practice rarely give the opportunity for return on investment. Every decision related to investments aimed at improving voltage in the network should be preceded by a detailed technical and economic analysis of various solutions to the problem.

4. IMPACT OF VOLTAGE REGULATION ON NETWORK LOSSES The impact of changes in voltage on the network demand is described by the static voltage characteristics of network demand [1, 2, 9]. In the case of minor voltage deviations (±5% Un), changes in network demand are described by coefficients of voltage static characteristics of the network active demand α and reactive demand β. These coefficients show the percentage shift of active and reactive network demand by one percent voltage change. According to [2] the active and reactive network demand on real voltage Ur may be calculated using approximated relationships: (7) (8) where: Pr, Qr – are active and reactive network demand at real voltage Ur respectively; Pn, Qn – active and reactive network demand at nominal voltage respectively; α, β – factor of voltage static characteristics of active and reactive demand respectively; Un – nominal voltage; δU – deviation of supplying voltage: (9) The value of angle factor of voltage static characteristics of active power drawn from the network is given in Table 3 with the value of coefficient of voltage static characteristics of reactive power given in Table 4. Table 3. The value of factor of voltage static characteristics of active demand α for selected types of power distribution systems

Types of power distribution systems

Source:

Value of factor of voltage static characteristics of active demand α within hours of:: Morning peak load

Evening peak load

Night load

[2]

0.90÷1.20

1.50÷1.70

1.50÷1.60

[2]

0.60÷0.70

1. 40÷1.60

Rural networks

[2]

0.50÷0.68

1.50÷1.60

20 kV network of Distribution Company X

[1]

1.20

1. 46

–

15 kV network of Distribution Company Y

[9]

1.15

2.25

0.95

Grid suppluing big towns with small industrial consumers Grid suppluing small towns with small industrial consumers

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow Table 4. The value of angle factor of voltage static characteristics of reactive power β for selected consumers, with voltage deviation in the range ±5%Un Types of power distribution systems

Source:

Value of factor of voltage static characteristics of reactive demand β within hours of: Morning peak load

Evening peak load

Night load

[2]

3.00

2.60

3.10

[2]

3.00

2.60

3.10

Rural networks cosφ ≥ 0.85 0.80 ≤ cosφ < 0.85 0.70 ≤ cosφ < 0.80 cosφ < 0.70

[2]

2.30 2.50 2.80 3.10

2.60

3.10

20 kV network of Distribution Company X

[1]

2.85

4.14

–

15 kV network of Distribution Company Y

[9]

5.95

2.60

2.30

Grid suppluing big towns with small industrial consumers Grid suppluing small towns with small industrial consumers

The impact of supplying voltage changes as well as transformation ratio control on network demand, power and energy losses can be traced on the example of a simple medium voltage circuit comprising of a medium voltage line, MV/LV transformer and low voltage demand. The circuit and equivalent diagram are presented in Fig. 2. Voltage on consumer terminals may be changed by changing the supplying voltage Uz and/or position of the transformer tap changer resulting voltage deviation δUzT. Various combinations of input voltage changes and transformer ratio control are possible. Two cases involving extreme changes are given below: a. changes of input voltage Uz with simultaneous changes position of the transformer tap changer by δUzT, so that the voltage on the consumer terminals Uo remains unchanged b. changes of input voltage Uz with no adjustment of transformation ratio control so resulting in voltage change on the consumer terminals Uo

Fig. 2. Medium voltage circuit and its equivalent diagram

4.1. Adjusting input voltage with simultaneous changes of transformer ratio control Simultaneous changes in input voltage feeding the network and change of transformer ratio control so that voltage in consumer terminals remains unchanged Uo = const – power (and energy) supplied by the network for delivery remains the same. However, the following changes take place: • current in the supply line – inversely proportional to voltage change • power loss of transformer idling – proportional to the square of voltage change value. Changing current causes change a load loss in the circuit – proportional to the square of that change. Loss of energy in the circuit is also subject to change. In this case the direction of loss change depends on: the direction of changed voltage, circuit load and volume of transmitted energy.

Optimal Voltage Control in Medium Voltage Power Engineering Networks

Relative change of energy loss, [%]

Example 1. For the transmission system as in Fig. 2 energy loss was calculated in three variants differing in terms of line input voltage Uz and the location of the transformer tapping switch. Variant „Un”: Uz = Un = 15.0 kV, tapping switch position δUzT = 0% Variant „1.05Un”: Uz = 1.05Un = 15.75 kV, tapping switch position δUzT = – 5%” Variant „0.95Un”: Uz = 0.95Un = 14.25 kV, tapping switch position δUzT = +5%. In the case of such line input voltage and transformer tapping switch positions the output voltage in consumer terminals remains the same for every variant. For each variant calculations were performed using following data: line elementary impedance R0 = 1.227 Ω/km, elementary reactance X0 = 0.398 Ω/km, line length l = 1 km; three values of utilization periods of maximum losses: τ = {1 670; 2 580; 3 560} h/a. (which corresponds to the following utilization periods of peak load: Ts = {3 000; 4 000; 5 000} h/a; transformer load changes range from 25 to 625 kW with power factor cosφ = 0.94; transformer parameters: rated power Sn = 630 kVA, rated transformer ratio ϑn = 15,0/0, 4 kV, load loss Pk = 6.1 kW, no load loss P0 = 0.97 kW, short circuit voltage uk = 6%, idle current i0 = 1%. Calculation results are given in Fig. 3 in graph form showing the relative changes in energy loss in the transmission system in terms of transformer load. The chosen point of reference was the energy loss in the system (corresponding to the given load) calculated at zero voltage deviation (Variant „Un”).

Transformer demand factor, [%Sn]

Fig. 3. A relative change of energy loss as a function of transformer demand factor in the case of simultaneous changes supplying voltage and transformation ratio control

The graphs show that when the transformer is underloaded an increase in input voltage concurrent with the same relative increase of transformer ratio cause energy loss in the system. The loss increases with the decrease in transformer load and the shortening of time intervals of peak power consumption. For example in result of growing input voltage and transformation ratio by 5% and transformer load of So = 30% Sn and time values for peak power consumption Ts = 3 000 h/a, energy loss grows by less than 8.5% and in time value Ts = 5 000 h/a circa 6.5%. Relative loss changes diminish with growing transformer load (when the transformer load exceeds a speciﬁc value the direction of change switches to the opposite sign, i.e. losses decrease with growing voltage). On the basis of graphs in Fig. 3 we can state that in the case of adjustments involving simultaneous changes of input voltage and transformer ratio, a change in energy loss direction in the system depends above all from the system load and time intervals of peak power consumption. In the case of small load and short time intervals of peak power input voltage should be decreased and simultaneously the transformer ratio reduced in order to reduce losses. In contrast, with big loads and long time intervals of peak power consumption, input voltage and transformer ratio should be increased. On the other hand, the comparison of calculation results for two line lengths indicates that losses decrease with falling transformer loads – resulting from the impact of bigger voltage drop on transformer idle loss.

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

Fig. 4 shows the range of load power factor cosφ depending on the value of factor of voltage static characteristics of the active power α, when load loss of power in the circuit fall with the growing voltage. The curves represent three values of factor of voltage static characteristics of reactive power β. The curves are constructed so that the intersection point of the straight line, representing load power factor value cosφ, with the straight line representing the value of factor of voltage static characteristics of the active power α, lies above the curve representing the value of factor of voltage static characteristics of the reactive power β, then load power loss in the circuit diminishes with the growing voltage.

1.00

Power factor cosφ

0.95 0.90

6.0 2.6 2.3

0.85 0.80 0.50

0.55 0.60 0.65 0.70. 0.75 0.80 0.85 0.90 0.95 Factor of voltage static characteristics of active power α

1.00

Fig. 4. Range of power factor cosφ in terms of factor of voltage static characteristics of active power α, when load loss of active power decreases with the growing voltage

Table 3 indicates that the factor of voltage static characteristics of the active power α is less than one in principle only during the morning peak load when the value of load power factor is low (power factor values cosφ in MV networks are given in Table 5). In practice this means that situations of network load loss decrease while supplied voltage grows occur very rarely. Table 5. Power factor cos� in medium voltage network in various seasons, days and hours [15] Kind of network

Season (daytime)

Network supplying big town

Network supplying rural areas

Power factor cosφ Before noon

In the evening

At night

Winter (workday)

0.86

0.89

0.77

Summer (workday)

0.74÷0.80

0.63

Winter (workday)

0.50÷0.70

0.98

Summer (workday)

0.52÷0.67

0.78÷0.98

0.90÷0.98

Summer (Sunday)

0.88

0.98

0.78÷0.93

Generally, input voltage growth accompanies growth of load losses in the circuit. Only in the cases of high power factors cosφ, in that time of the day when the factor of voltage static characteristics of the active power α < 1, the load losses may decrease with the growing input voltage. When the factor α ≥ 1, load losses always grows together with growing supplying voltage (because of the factor α is always bigger than 1). As the factor of voltage static characteristics of the active power is always bigger than zero, growing supplying voltage will always be accompanied by the growth of active power consumption. In most cases (except for consumers requiring a ﬁxed amount of energy for their technological process) the amount of energy used by the consumers also grows.

Optimal Voltage Control in Medium Voltage Power Engineering Networks

4.2. Adjusting input voltage with no change of the transformer ratio control Whereas the change of input voltage is not accompanied by a change of the transformation ratio, voltage changes in consumer terminals. The relative changes by δU in the supplying voltage supplying the circuit will cause almost the same relative voltage changes on the transformer terminals and consumer terminals. As a result of above voltage change the next changes will take place: • of the consumed active and reactive power supplied by the network – in compliance with the voltage static characteristics of the consumed power • of energy consumed from the network • power loss of transformer idling. Changes in the delivered power consumed result in changes of the current in the circuit, and thus the load loss. The direction changes of total power loss in the circuit depend on the power factor, ratio of transformer load and time of the day.

Relative change of energy loss, [%]

Example 2. Similarly as in example 1, calculations were made for the transmission system of power changes and energy consumed from the network, power and energy losses in the system with rated transformation ratio for three values of supplying voltage (the same as in example 1). Other parameters used in the calculations were the same as in example 1. Fig. 5 shows relative changes in energy loss against energy loss at rated voltage.

Transformer demand factor, [%Sn]

Fig. 5. A relative change of energy loss as a function of transformer demand factor in the case of changes supplying voltage and ﬁxed transformation ratio

Fig. 5 indicates that an increase of input voltage by 5% causes growing power and energy loss of over 10%, whereas a 5% voltage drop leads to a nearly 10% reduction of power and energy loss.

4.3. Conclusions The deliberations presented above indicate that: 1. Voltage regulation in distribution networks have an impact on both power and energy loss in the network and power and energy consumption from that system, and thus on company costs and revenues. 2. In extreme cases voltage regulation, reducing power and energy loss, may result in decreasing the amount of energy used by consumers and thus reduce revenues for transmission charges. We should emphasise that the example selected well depicts the nature of changes in progress. In real network circuits supplying a bigger number of stations, operating under varied loads and time of peak consumption, the situation is not as clear. In order to determine the input voltage level and MHV/LV transformer ratio setting that is the most appropriate, in terms of loss, MHV/LV transformer ratio requires optimising calculations.

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

5. OPTIMAL VOLTAGE CONTROL The key objective of voltage regulation is assuring voltage deviation in every point of the medium and low voltage networks within the admissible range. In the process of achieving this objective we can also optimise the voltage level in the network. The solution for optimising voltage regulation comes down to finding voltage values for MV busbars in DS feeding the network and all MV/LV transformation ratio setting values, where the target function of a specified quality control criterion reaches the optimum and is concurrently compliant with limitations resulting from admissible voltage deviations and technical capacity to effect the control (e.g. transformation ratio control range). The number of targeted voltage values for MHV busbars depends on the number of time zones per day The setting of MV/LV transformer tapping switches is the same for all time zones in the analysed period. Calculations are performed for the period of a year or separately for particular seasons, e.g. autumn/ winter and spring/summer. The solution for optimum voltage control for networks feeding n TS in time T, comprising r time intervals, is the vector determining all MV/LV transformer tapping switches settings in the analysed network, containing information on the relevant level of input voltage in DS where the target function of adopted optimum criterion reaches an extreme value. (10) where: δUzTi – voltage deviation connected with the position of the MV/LV transformer tapping switch in i station; δUzp – oltage deviation in MV busbars in DS connected with the position of the medium to low voltage 110 kV/MV transformer tapping switch in time interval p. If we assumed optimisation for a period of one year broken down to hours, the number of input voltage levels in DS to be identified would be huge and amount to r = 8 760. Thus, the vector (10) would be very long and the problem difficult to solve. Therefore, the need for decomposition. Decomposition of the problem involves a breakdown of the hourly sets to a small number of subsets called zones, where a fixed input voltage level in DS is assumed. This corresponds to agreeing on network load intervals for which input voltage to DS remains constant. Usually several (4–6) such zones are agreed. In this situation the solution vector takes the following form (11) where s – the number of time zones, s << r.

5.1. Optimum voltage regulation criteria It is possible to formulate varied criteria for optimum voltage regulation: (1) minimising costs of economic losses for consumers resulting from voltage deviation from nominal value [14]: min KOdb

(12)

(2) minimising costs of power and energy loss in the network of the distribution company [18, 19]: min KS = min (KΔP + KΔE)

(13)

(3) minimising costs of the distribution company, i.e. costs of power and energy loss in the network and costs of discounts and allowances granted to consumers for failure to control voltage deviation in the admissible range [18, 19]: min KD = min (KS + KB)

(14)

Optimal Voltage Control in Medium Voltage Power Engineering Networks

(4) minimising relative energy losses in the network [18, 19]: (15) (5) maximising proﬁts of the distribution company for the sale of power [18, 19]: max ZD = max (DS – KZ)

(16)

(6) minimising joint costs (total), i.e. costs of power and energy loss in the distribution company’s network and economic losses incurred by consumers (minimising total costs in criteria (1) and (2) [18, 19]: min KC = min (KS + KOdb)

(17)

(7) minimising voltage deviation at the consumers [5, 6 and 7] min ∑δU2

(18)

where: KΔP – power loss costs; KΔE – energy loss costs; ΔE – energy losses in the network, E –energy fed to the network; Ds – revenues generated by the sale of energy; KB – cost of discounts and allowances granted to consumers for exceeding admissible limits; Kz – purchase costs of energy from 110 kV network, KOdb – costs incurred by consumers in result of voltage deviation from rated value; ΣδU2 – the sum of voltage deviation square at the consumers in the analysed time intervals. While we optimising using criteria (1)÷(5) and (7) we accept voltage deviation that does not exceed permissible values expressed by inequality (3), whereas using criterion (6) voltage deviation beyond the admissible range is acceptable. Nevertheless, each criterion must comply with restrictions resulting from technical conditions like e.g. limited range of transformer tapping switches or permissible voltage in terms of insulation strength. The mathematical model (in the form of target function and constraints conditions) of optimising voltage regulation under criterion (1) was presented in a PhD thesis [14]. Mathematical models for optimising under criteria (2) ÷ (6) are presented in detail in the papers [18, 19]. The target function accounts for the impact of changes in voltage on network demand (in accordance with the voltage static characteristics of consumed power). To solve the problem of optimising voltage regulation in the distribution network a specially constructed neural network was applied. A detailed description of an optimising method under criterion (7) can be found in the papers [5, 6 and 7]. In this case special computer software based on evolutionary algorithms [3, 10] was developed to solve the problem of optimum voltage control in the distribution network.

5.2. Input data for calculations In order to calculate the optimum voltage on medium busbars in DS feeding the network and to choose the setting for MV/LV transformation ratio control according to the optimising criteria given above, the following data on the optimised network is required: 1. network connection scheme and parameters of particular MV lines (length of sections, cable diameter or unit line resistance and reactance) 2. rated parameters of MV/LV transformers installed at the transformer stations, i.e. rated demand, rated voltage of primary and secondary windings, rated load loss (cooper loss), short circuit voltage, possible tapping switch positions and related transformation ratios 3. demands of particular transformer stations (or information required to determine that demands) 4. possible tapping switch positions and and related transformation ratios of 110 kV transformer feeding the network

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

100

5. annual demand proﬁle of 110 kV transformer feeding the network. In In the case of criteria (2) to (6), taking into account the impact of voltage regulation on network demand, additional data is required: 6. value of coefﬁcients of voltage characteristics of active demand α and reactive demand β 7. rated no-load loss (iron loss) of active power in iron (idle loss), no-load current idle current of MV/LV transformers 8. information referring to economic losses incurred by consumers in result of voltage deviation.

6. EXAMPLES OF CALCULATIONS FOR REAL NETWORKS 6.1. Optimisation accounting the inﬂuence of voltage changes on network demand Calculations were performed for a real 15 kV network fed by 110/15 kV distribution substation applying the criteria (2)÷(6), referred to in the paragraph above. The network is located in the south of Poland. Example 3. The 15 kV network, fed by a 110/15 kV distribution substation (DS X) comprises 7 circuits total length circa 168 km. These circuits supply 136 15/0. 4 kV transformer stations of total rated demand of transformers of 13 MVA. A topographic diagram of the network is given in Fig. 6 and characteristic data of particular circuits is presented in Table 6. Table 6. Basic parameters of MV network circuits supplied by DS X [18] Number of MV/LV transformer stations supplied [pcs]

Total rated demand of MV/LV transformers [kVA]

Length of MV line [km]

Average cable cross-section of MV circuits lines [mm2]

1 472

19.2

34. 4

1 699

28.8

33.7

2 604

41.1

41.0

1 760

24.2

31.9

2 038

29.1

30.2

389

7.2

44.2

1 456

18. 4

37.9

Total

136

11 218

167.9

35.6

Circuit no

The following optimising calculations were performed for this network: • voltage on MV busbars in DS for three time zones • setting tapping switches in all MV/LV transformers supplied by the network • value of target function according to criteria (2), (3), (4) and (5). Calculations were performed for the autumn/winter season broken down to three day time zones, i.e. morning peak – sr, evening peak – sw and other hours of the day (off peak zone) – sp. The circuit load was assumed as for the winter peak network load. Value of factor of static voltage characteristics of active and reactive demand was assumed according to [2]. The assumed initial conditions for the calculations were the same, for all three time zones voltage on MV bus bars in DS equal to Usr = Usw = Usp = 15.3 kV and the tap switch position of all 15/04 kV transformers in position δUzT =0. These conditions satisﬁed all the constraints (voltage ranged within permissible values), and the target function was calculated for criterion (5) on minimizing total loss and amounted to PLN 248.7 thousand. Cost calculations assumed: power unit costs at 67.56 PLN/kW a and energy unit costs in morning peak hours at 115.23 PLN/MWh. evening peak hours at 188.31 PLN/MWh, and off peak hours at 57.61 PLN/MWh.

Optimal Voltage Control in Medium Voltage Power Engineering Networks

101

Key – 15/04 kV transformer station No – X401 – DS X

Fig. 6. A topographic diagram of the 15 kV network fed by DS X [19]

The basic calculation results are presented in Table 7. The Table shows the optimum voltage (for each of the four criteria) that should be maintained in particular periods of the day on MV busbars in DS and target function value prior to and following optimisation. It should be noted that the calculations were only performed for the autumn/winter season from October 1 to March 30. Table 7. Results obtained applying various optimising criteria [19] Optimum voltage on MV busbars in DS Criterion

Usr [kV]

Usw [kV]

Tapping switch setting1)

Usp [kV]

δUzt [%]

Target function value initial

optimum

57.2

54.0

Unit

(2) minimum costs of power And energy losses

14.54

14.67

14.58

+2.5 or +5.0

(4) – minimum relative loss

15.75

0.0

3. 483

3. 475

(5) – maximum proﬁt

15.28

15.25

15.75

0.0

1 354.0

1 413.6

Thous. PLN

(6) – minimum total costs

14.37

14.51

14.52

+2.5 or +5.0

250.3

207.2

Thous. PLN

1) A voltage increase in percentage share is given resulting from setting tapping switches . „+2.5” or „+5” means that transformer tapping switches should be set so that voltage grows by 2.5% or 5%, and „0,0” means that tapping switched in all transformers should be in neutral position (the program calculated the optimum tapping switch settings for particular stations).

Aleksander Kot / AGH University of Science and Technology in Cracow Waldemar L. Szpyra / AGH University of Science and Technology in Cracow

102

On the grounds of results given in Table 7 we can draw the following conclusions: 1. The improvement of voltage regulation quality indicator is possible by applying the optimising criterion. 2. Depending on the used optimising criteria we obtain indications for voltage levels on MV busbars in DS and settings for transformer tapping switches. 3. Various criteria may be selected depending from the point of view: • in terms of company interests, distribution companies should control voltage according to criteria (2), (4), (5) or (6) • in terms of social costs voltage should be controlled according to criteria (1) or (7). 4. Optimisation according to criteria (6) allows the admissible voltage deviation to exceed the rated value, which could be beneficial for distribution companies when system regulation requirements stipulate mandatory investments in the network. This also derives from the rules for calculating discounts for exceeding admissible voltage deviations. 5. Optimisation under criterion (1) has no practical application as it is difficult to assess economic costs related to voltage deviation. 6. With the restructuring of the energy sector and breaking up into energy trading companies criterion (5) loses significance for network companies. Criteria (1) and (5) may be substituted by criterion (7).

Adapting

6.2. Optimum voltage regulation according to the criterion of minimising voltage deviation at the consumer’s Below is a very brief example of optimising voltage regulation according to the criterion of minimising voltage deviation at the consumer’s in a real network, cooperating with off grid generated sources. A program dedicated for the purpose was used to perform the optimisation calculations. A real model has been developed of a 110 /15kV distribution substation located on the area of one of the distribution companies in the southern part of Poland. It feeds 156 medium/low voltage transformer stations supplied by 4 circuits (circuit length: 3÷95, km, number of stations 6÷83). To the biggest circuit connected a water power plant of attainable power reaching 1050 kVA. Network is supplied by 110/15 kV transformer of rated demand 16 MVA and voltage control range of of +/– 16% with distribution capacity of 1.78%, and resultant +/– 9 positions of the tapping switch. A registered annual load history was used with an imposed random power generation history of the power plant. Optimum parameters of the evolution algorithm was attained applying a population of 200 individuals in 9000 generations, probability of crossing 0.9, probability of mutation 0.01. The calculation time for one algorithm processing lasted circa 4 hours. (processor AMD Athlon 2000XP). A typical optimising process for three program cycles is presented in Fig. 7.

Cycle 1 Cycle 2 Cycle 3

Generation number

Fig. 7. Optimising process for 3 calculation cycles

Optimal Voltage Control in Medium Voltage Power Engineering Networks

Optimising calculations were made for the presented facility using a program assessing load history with randomly imposed generation for two seasons – winter and summer. Particular studies provided solutions for adapting to: winter season 689 181. 4 summer season 707 320. 4 The solution comprises a set of optimum settings for tapping switches of all MV/LV transformers and optimum supply voltage on medium voltage busbars in DS for all time zones. Due to the length of the vector, full solutions are not given but only adapting values. The selection of optimum setting for tapping switches of all MV/LV transformers in the distribution network of a given facility allows us to proceed to the next stage. This stage involves continuous voltage regulation in DS for every time interval, taking into account the network load and generation power at source.

110/15 kV Transformer tapping switch no

Generation coefﬁcient g

Load factor w

Fig. 8. Optimum voltage in DS in terms of network load and generated power – winter season

110/15 kV Transformer tapping switch no Generation coefﬁcient g

Load factor w

Fig. 9. Optimum voltage in DS in terms of network load and generated power – summer season

Figures 8 and 9 present the optimum input voltage to the network in DS (tapping switch number) in terms of network load and power generation coefﬁcient for the winter and summer season respectively. The solution to the problem of voltage regulation in the distribution network, including off grid sources is possible by applying techniques based on evolutionary algorithms. The appropriate choice of parameters in

103

104

Aleksander Kot / Akademia Górniczo-Hutnicza w Krakowie Waldemar L. Szpyra / Akademia Górniczo-Hutnicza w Krakowie

the calculation process allows for solutions of adequate precision and repetitiveness in case of diversified initial population. The introduction of heuristic elements to the calculations (knowledge of problem properties) allows for acceleration of optimum solution results. The calculation tool can be applied both for distribution networks including sources as well as reactive networks. Off grid generation in the MV network has an impact on the voltage regulation system (MV/LV transformer tapping switch settings and DS voltage). The presence of randomly operating power sources deteriorates voltage regulation conditions. Optimal choice of tapping switches sets, with the participation of power generation, of MV/LV transformers, which regulate DS voltage, allow for minimising the number of tapping switch connection in the 110kV/MV transformer. The influence of changes in power generation in off grid sources on the 110/MV transformer voltage regulation depends on the distribution network structure, load, location of off grid generating units and the power generated and supplied to the network. Sources of lesser power feeding the 15 kV distribution station located nearby have a negligible impact but the influence becomes apparent with growing distance of the busbars connection point and generated power. In terms of DS voltage control, the number of stations in the circuit/circuits with generation to the total number of stations supplied by a given 110 kV/MV transformer is significant. It is determined by the form of the applied target function. The characteristics of optimum voltage regulation in DS, in terms of network load and power generation in off grid sources, may give grounds to a decision to equip a given facility with a follow up voltage regulation system of the 110/MV transformer based on continuous estimation of voltage conditions of the input distribution network taking into account the present network load and the generated power of cooperating generating units. In order to implement input voltage regulation in a network with changeable load in DS (for MV network with no generation) the application of current compensation is suggested for the 110 kV/MV transformer voltage regulation. Identification of proper compensation parameters is possible basing on results of the program referred to above and the voltage model of the analysed network. Compensation parameters R and X and the voltage U after the compensation impedance is selected to obtain the optimum voltage changes on MV busbars in DS in the entire range of the annual 110 kV transformer load feeding the network.

7. SUMMARY Summing up the deliberations referring to control and optimisation of voltage in the distribution network, we can note the following observations. Voltage regulation in the distribution network influence power and energy consumption and losses in the network. The nature of this influence was analysed in part 4 of the article on relatively simple examples. In real circuits supplying a bigger number of stations, the identification of the most appropriate, in terms losses, input voltage to the network and tapping switches settings for the MV/LV transformers requires optimising calculations. These requirements on voltage deviation in the network are included in “system regulations” [17]. The permissible voltage deviation range for a network operating without disturbance is specified so the present regulations in force regarding voltage conditions in distribution networks are more liberal than those mandatory prior to the regulation. Voltage drop and deviation balance indicates that the use of the full voltage regulation range in DS can ensure the required voltage delivered to LV customer from a MV network in the case of a voltage drop of up to 7.5% in the MV network. The primary means of voltage regulation in distribution networks is exploitation of 110 kV/MV and MV/LV transformation ratio control. Application of additional technical means to reduce voltage drop requires considerable investment outlays, which in practice rarely give the opportunity for return on investment. We can formulate various optimising criteria for voltage regulation which have been described in more detail in item 5.1. An analysis of a real network indicates that depending on the adopted optimising criteria we obtain indications for voltage levels on MHV bus bars in DS and setting transformer tapping switches.

Optimal Voltage Control in Medium Voltage Power Engineering Networks

The selection of the appropriate criterion for optimum regulation is discussed in the conclusions following item 6.1. With the restructuring of the energy sector and introduction of market instruments, minimising voltage deviation at the consumer’ seems to be gaining on significance. Effective solutions for optimum voltage regulation in real distribution networks involve techniques classified as artificial intelligence methods, i.e. artificial neuron networks and evolutionary algorithms. Computer software developed for optimising voltage regulation using the techniques described above are not products for commercial operations.

LITERATURE 1. Biniek M., Kinsner K., Łabuzek M., Pomiarowe wyznaczanie napięciowych efektów regulacyjnych mocy czynnych i biernych w systemie elektroenergetycznym, Zeszyty Naukowe Wyższej Szkoły Inżynierskiej w Opolu, Seria Elektryka z. 42, Opole 1995, pp. 53–60. 2. Bogucki A., Lawera E., Przygrodzki A, Szewc B., Podatność częstotliwościowa i napięciowa systemu elektroenergetycznego i jego elementów, Politechnika Śląska, Skrypty uczelniane No 1116, Gliwice 1983. 3. Goldberg D., Algorytmy genetyczne i ich zastosowania, Wydawnictwa Naukowo-Techniczne, Warszawa 1998. 4. Instrukcja ruchu i eksploatacji sieci przesyłowej. [Instruction of Transmission System Operation and Maintenance] Warunki korzystania, prowadzenia ruchu i planowania rozwoju sieci, version 1.2, consolidated text valid as of 5 November 2007 PSE – Operator S.A. 5. Kot A., Ewolucyjna optymalizacja regulacji napięcia w rozległej sieci rozdzielczej zawierającej lokalne źródło mocy, Przegląd Elektrotechniczny No 9/2006, pp. 124–126. 6. Kot A., Optimal voltage control in the medium voltage networks containing dispersed generation, Archiwum Energetyki, tom XXXVII (2007), No 1–2, pp. 261–276. 7. Kot A., Optymalna regulacja napięcia w sieciach średniego napięcia zawierających źródła generacji rozproszonej, praca doktorska [doctorate disertation] AGH, Kraków 2005. 8. Kot A., Program komputerowy do optymalizacji regulacji napięcia w rozległych sieciach rozdzielczych, Energetyka, Zeszyt tematyczny No XIII, pp. 96–100. 9. Lipart K., Charakterystyki statyczne mocy, praca dyplomowa[diploma thesis] AGH, Faculty EAiE, Kraków 1996. 10. Michalewicz Z., Algorytmy genetyczne + struktury danych = programy ewolucyjne, WNT, Warsaw 2003. 11. Standard PN-88/E-02000, Napięcia znamionowe. 12. Standard PN-EN 50160: Parametry napięcia zasilającego w publicznych sieciach rozdzielczych [Voltage Characteristics in Public Distribution Systems], Polski Komitet Normalizacyjny, December 2002. 13. Standard PN-IEC60038:1999, Napięcia znormalizowane [Standard Voltages]. 14. Piotrowski P., Optymalizacja regulacji napięć w elektroenergetycznych sieciach rozdzielczych w oparciu o teorię sieci neuronowych, rozprawa doktorska, Politechnika Warszawska Wydział Elektryczny, Warsaw 1994. 15. Popczyk J., Żmuda K., Sieci elektroenergetyczne. Ocena stanu i optymalizacja według podejścia probabilistycznego, Skrypty Uczelniane Pol. Śl., Gliwice 1991. 16. Ordinance of Minister of Economy of 2 July 2007 on detailed rules of calculation of tariffs and power supply/demand settlements (Journal of Laws of 18 July 2007, No 128, pos. 895). 17. Ordinance of Minister of Economy of 4 May 2007 on detailed conditions of functioning of electrical power system (Journal of Laws No 93 of 29 May 2007, pos. 623). 18. Szpyra W., Optymalna regulacja napięcia w rozległej sieci rozdzielczej średniego napięcia, Archiwum Energetyki, tom XXIX (2000), nr 1–2, pp. 27–47. 19. Szpyra W., Optymalna regulacja napięcia w rozległej sieci rozdzielczej średniego napięcia, praca doktorska [doctorate dissertation], Akademia Górniczo-Hutnicza, Kraków 1998. 20. Szpyra W., Optymalna regulacja napięcia sieci rozdzielczej średniego napięcia w warunkach rynkowych, in: Wilkosz K. (ed.), Problemy systemów elektroenergetycznych, Polska Akademia Nauk, Komitet Elektrotechniki. Seria wydawnicza Sekcji Systemów Elektroenergetycznych Komitetu Elektrotechniki PAN, Oﬁcyna Wyd. Pol. Wrocławskiej, Wrocław 2002, Chapter 16, pp. 409–433. 21. The Act of 10 April 1997 – The Energy Law, consolidated text: Journal of Laws of 2003, No 153, item 1505, with later amendments. 22. Guidelines for programming development of distribution networks, Instytut Energetyki, Zakład Sieci Rozdzielczych, Warszawa – Katowice 1986.

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Authors / Biograﬁes

Krzysztof Wilde Gdańsk / Poland Graduated from the Faculty of Civil Engineering of Gdańsk University of Technology in 1989. Six years later he successfully presented his PhD thesis at Tokyo University in Japan. In the period of 1996–1999 he worked as an associate professor at Tokyo University. In 2002 he was awarded the degree of habilitated doctor, and in 2009 – the title of professor. Now he is employed as a professor. He research interests focus on dynamic sensitivity of structures, active and passive vibrations of bridges and nondestructive diagnosis of engineering structures.

Structural Health Monitoring for Power Transmission Lines – Global Damage Detection Method

DYNAMICS OF FAULT ARC TRAVELING ALONG BUSBARS IN HIGH VOLTAGE SWITCHBOARDS Krzysztof Wilde / Gdańsk University of Technology

1. INTRODUCTION Surveillance may be understood as a set of processes of identification, tracking, analysis and response which organize the considered problem. Surveillance became one of the most important issues in terrorism detection and public health monitoring. The data on market trends as well as customer preferences is gained through extensive surveillance infrastructure. The most common civil engineering application of surveillance technologies are systems for air transportation, where the principal goal is to ensure the safe, expeditious and economical performance of air traffic. The developed countries use traffic surveillance technologies for car traffic management that plays an essential role in incident detection and travel time collection. Most of the applied solutions are based on set of surveillance cameras, dedicated software for video image detection and other sensing technologies. The surveillance systems are also used in civil structures of special importance, where a catastrophe can lead to extensive financial, environmental or human losses. While surveillance aims at broad activities ranging from social behaviors to physical or financial processes, the term Structural Health Monitoring (SHM) refers to collection and analysis of selected structural parameters. Civil infrastructure, in most countries, consists of a large number of ageing buildings, towers, bridges, tunnels, dams and other structures, which require regular inspections to ascertain their safety. The visual inspections might be reinforced by non-destructive testing. The early and precise detection of damage allows to undertake appropriate repair measures before the damage deteriorates to the extent of making the structure unserviceable. The SHM systems become obligatory, in many countries, also for new infrastructure, particularly for large structures with very high initial construction costs. The structures implemented with continuous damage detection systems can considerably extend operation life. The value gained from improved structural performance justifies the costs of installation and operation of the SHM system. The SHM systems are dynamically developed in Asia, particularly in China, Japan, Singapore and recently also in Europe (Belgium, UK, Germany, etc.) as well as in the United States and Canada. Initially, the SHM systems in civil engineering structures were used in long span bridges [1] and very tall buildings. At present, the automated damage detection systems are installed in harbor protection structures, cooling towers, mountain and sub-sea tunnels, dams, and power stations (e.g., [2]). The need for the monitoring of structural elements of energy infrastructure has also been recognized. In 2008, the European Commission allocated 5 million Euros under the 7th Framework Program on “Intelligent” power transmission lines with focus on “Diagnostics, Surveillance, Maintenance and Control of Power Transmission and Grid Connections” (ENERGY.2008.7.2.3.). The effective use of SHM system requires a proper selection of nondestructive testing (NDT) method. Most of the available techniques are localized experimental methods, such as radiography, magnetic field, eddy current, ultrasonic, acoustic, or thermal field methods [7]. All of the mentioned methods can be used on relatively small parts of the structure. They require that the vicinity of the potential damage is known a priori and that the considered part of the structure is easily accessible. Large civil engineering structures, for example, Abstract Selected structural health monitoring (SHM) systems operated in Poland are presented in the paper. A successful application of SHM systems based on dynamic measurements and wavelet signal processing for steel plate is shown. The possible role of such systems for energy infrastructures are discussed on example of high voltage power transmission lines.

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dams or transmission towers do not satisfy this requirement. Recently, the global detection methods that can scan large complex objects have been extensively studied. The research has focused on vibration based methods [8], long range ultrasonic techniques [9] or terrestrial imagining that combines photogrammetric, 3D laser scanning and GPS tools (e.g. [10]). The aim of this paper is to present the possibilities of SHM systems for power transmission lines with focus on global damage detection systems based on vibration techniques.

Fig. 1. Conceptual design of structural surveillance

2. STRUCTURAL HEALTH MONITORING SYSTEMS The aim of the SHM system is to detect the appearance of the damage at the earliest possible time. The damage is deﬁned as changes to the material or geometrical properties of the structure that adversely affect the structure’s performance [3]. The simplest SHM is an expert technician who conducts regular visual inspections of the considered structure. The expert’s report is a base for decisions on structure maintenance (Fig. 1). In the case of complex structures like dams, visual inspections are facilitated by measurement data. For example, the dam near Wocławek has an automated data acquisition system [4]. The sensors net consists of piezometers, inclinometers, feeler gauge, water level sensors and temperature sensors. The total of 190 measurement points have been established. The system was activated in 1997 and it was designed to provide the measurement data at the dam site for the technical staff operating the structure. Large monitoring system has been installed by KGHM Polska Miedź S.A. at the tailing reservoir Żelazny Most [5]. The structure serves for waste storage from copper production and consists of a dam whose height is increased on demand. The purpose of the monitoring system is to assess the current technical state of the structure and its further safe development. At present, The monitoring system, has over 8000 measurement points collecting geological, hydrogeological, geotechnical, geophysical, chemical and geometrical data. The huge amount of data is stored in professional Oracle database integrated with GIS solutions. The monitoring system has all the tools for data selection and presentation. However, there seems to be only few accompanying programs for modeling the physical and chemical process that take the advantage of the collected data.

Structural Health Monitoring for Power Transmission Lines – Global Damage Detection Method

Fig. 2. Screen of the signalization module of SMT OLIVIA-2

The example of the SHM system with integrated numerical model of the structure is the SMT OLIVIA-2 system installed in Sports Arena “OLIVIA” in Gdańsk [6]. The system conducts online measurements at 74 locations and online simulations on FEM model of the roof. The automatic and continuous reports on the structure health are presented with respect to the critical allowable values and performance index describing the correlation between the measurements and numerical simulations. The signalization module (Fig. 2) presents online the most important information for the Arena technical staff. The module informs about correct state of the structure, sends warnings about minor problems or warns about the possible catastrophe. The signalization screen provides the results of the numerical simulations in terms of the representative thickness of the snow that causes current displacement of the roof. The view from the cameras focused on important roof elements located inside and outside Sports Arena are also included. The signalization module (Fig. 2) shows also the displacements of 4 roof girders for 3 days period. The SHM system is designed for the particular structure. The choice of sensors is determined by goals to be achieved and the characteristics of the engineering object. Structures prone to oscillations can be monitored via vibration-based nondestructive testing.

3. VIBRATION BASED SHM SYSTEM 3.1. Vibrations for nondestructive diagnostics The concept behind the vibration based methods states that damage signiﬁcantly alters the stiffness, mass or energy dissipation properties of the structure, and this in turn changes the dynamic responses of the tested object. Environmental loadings induce the vibrations of the cables and towers (Fig. 3). The data acquisition system records the acceleration time responses at several locations, and the natural frequencies and mode shapes are determined via experimental modal analysis. The changes in modal parameters allow indentifying the presence of the damage. In the case of signiﬁcant structure deterioration, the location of the damage can also be found.

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Fig. 3. Concept of vibration based structural health monitoring system

Although the idea of vibration based diagnostics seems obvious, its practical applications lead to problems. The main condition for effective application of such SHM system is dynamic sensitivity of the structure to the damage. A typical crack, flaw, injury etc. are local phenomena, and therefore, they might not significantly influence the global response of the structure.

3.2. Example of wavelet damage detection for steel plate Successful application of vibration based nondestructive testing is presented on an experimental study of a rectangular plate with ﬁxed supports. A steel plate of the length L = 560 mm, width B = 480 mm and height H = 2 mm is considered. The material properties were determined experimentally and are found to be: Young’s modulus E = 192 G Pa, Poisson ratio ν = 0.25 and mass density ρ = 7430 kg/m3. The plate (Fig. 4) contains a rectangular defect, induced by a high precision saw, of length Lr = 80 mm, width Br = 80 mm and depth a = 0.5 mm. The distances from the defect left-down corner to the plate left-down corner in the horizontal and vertical direction are: L1 = 200 mm and B1 = 200 mm, respectively. The area of the damage is 2. 4% of the plate area and the depth of the ﬂaw is 25% of the plate height.

Structural Health Monitoring for Power Transmission Lines – Global Damage Detection Method

Fig. 4. Experimental setup for the steel plate with ﬁxed supports

The force impulses induced by the modal hammer PCB 086C03 were applied to 143 regularly spaced locations. The vibration responses were recorded using one accelerometer attached to the plate at point No 74 on the plate bottom. The data acquisition system Pulse type 3650C was used for data measurements. Each recording of the acceleration and force was repeated ﬁve times and the results were ﬁve times averaged in the frequency domain. The estimation of the mode shapes was conducted through the H2(ω) estimator [11]. The plate mode shapes were computed by FEM program SOFiSTiK using the mesh of 40 40 mm plane elements. The frequencies for the plate obtained in the numerical simulations were f1 = 65.100 Hz, f2 = 120.00.100 Hz, f3 = 207.09.100 Hz and they were very similar to the frequencies obtained experimentally f1 = 64.875 Hz, f2 = 114.875 Hz, f3 = 195.25 Hz. The experimental and the numerical mode shapes of the plate are presented in Fig. 4. The black dots indicate the measurements, while the black lines show the numerical modes. The MAC values range from 0.9693 to 0.9967, indicating a very good agreement.

Fig. 5. Experimental and numerical 1st, 2nd and 3rd mode shapes of the steel plate

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three-dimensional view

top view

defect position

Fig. 6. Wavelet modulus computed from experimental mode shapes of the steel plate

The results of damage detection by using rbio 5.5 wavelet are given in Fig. 6. The wavelet coefﬁcient modulus Mf (u, v, s), computed on the experimental data, clearly indicates the defect position and its shape. The modulus is computed as square root of squares of 2D wavelet horizontal and vertical components. The details on this algorithm are given in [12]. The maximum of the modulus is in the distance of x = 240 mm and y = 243 mm from the left-down plate corner. The actual location of defect is x = 240 mm and y = 240 mm from the left-down plate corner.

3.3. Features of SHM system for power transmission lines The applicability of vibration based SHM system to power transmission lines (towers and cables) has been highlighted [15]. Due to relatively low stiffness, the transmission towers are very sensitive to dynamic loading, such as wind action. Most catastrophes of transmission towers are due to ice coating and snow storms (e.g. [14] [15]). Additional mass from ice is relatively large [13], and therefore, signiﬁcantly changes the dynamics of the tower-cable system. Thus, the main condition for successful application of vibration based SHM system is fulﬁlled. The mass added by the atmospheric acing as well as wind action has been found to be one of the most important reason for the transmission towers failure near Szczecin in 2008 [14]. The example of the domino effect catastrophe of the towers 124-129 of 220 kV, line Morzyczyn-Police, is shown in Fig. 7. In total, 41 transmission towers collapsed and two main types of failure were recognized: overturning and bending of tower structural elements. The conclusions from the Szczecin blackout 2008 indicated the need for validation of design code assumptions for transmission towers.

Fig. 7. Failure of towers 124-129 of 220kV line Morzyczyn-Police (courtesy of Teresa and Wiesław Paczkowski, Zachodniopomorski Uniwersytet Techniczny, [14])

Structural Health Monitoring for Power Transmission Lines – Global Damage Detection Method

The structural health monitoring system for transmission lines should not be designed only for operational safety enhancement but should also fulﬁll the following additional tasks: 1. provide data for improvement of design speciﬁcations and guidelines for new structures 2. detect abnormal events in existing structure responses and external loadings 3. detect the damage at the earliest stage 4. provide real time information and warnings on extreme events 5. support safety assessment immediately after disasters 6. provide data for planning the inspections 7. provide data for transmission line maintenance, repair or modernization.

4. CONCLUDING REMARKS A large number of existing transmission lines reach their service lives and the decisions of modernization have to be made. The data from either short time or long time SHM systems might be very useful to support the search for the most economical solutions. At present, structural health monitoring has been a subject of research for major international institutions and research groups. The work on SHM system covers sensing, communication, signal processing, data management, system identiﬁcation, structural design and construction. The challenge is to wisely and effectively adapt the innovative technologies developed in wide range of disciplines for the structural monitoring purpose.

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LITERATURE [1] Ko, J.M.; Ni, Y.Q., Technology developments in structural health monitoring of large-scale bridges Engineering Structures Volume: 27, Issue: 12, October, 2005, 1715-1725. [2] Liu, D.A.; Yang, Z.F.; Tang, C.H.; Wang, J.; Liu, Y., An automatic monitoring system for the shiplock slope of Wuqiangxi Hydropower Station Engineering Geology Volume: 76, Issue: 1-2, December, 2004, 79-91. [3] Robertson A., Farrar C., Sohn H., Singular detection for structural health monitoring using holder exponents, Mechanical Systems and Signal Processing, 2003, 17(6), 1163-1184. [4] Selerski S., Chmielewska I., Automatyczne systemy technicznej kontroli zapór (ASTKZ) Dębe, Włocławek i Wióry- podobieństwa i różnice. Bezpieczeństwo zapór – bezpieczeństwo ludności i środowiska, Monograﬁe Instytutu Meteorologii i Gospodarki Wodnej, str. 98-112. 2009 (in Polish). [5] Świdziński W., Świerczewski W. and Janicki K., Rozbudowa obiektu Hydrotechnicznego oparta na metodzie obserwacyjnej na przykładzie składowiska Żelazny Most. Bezpieczeństwo zapór – bezpieczeństwo ludności i środowiska, Monograﬁe Instytutu Meteorologii i Gospodarki Wodnej, str. 98-112. 2009 (in Polish). [6] Wilde K., Rucka M., Chróścielewski J., Jasina M., Malinowski M., Miśkiewicz M., Wilde M., System ciągłej obserwacji stanu technicznego hali „Olivia” w Gdańsku, Inżynieria i Budownictwo, 10/2009 (in Polish). [7] Docherty J., Handbook on Experimental Mechanics, Bethel, CT: Society for Experimental Mechanics Inc., Chapter 12, Nondestructive evaluation, 1987. [8] Cawley, P., Defect location in structures by a vibration technique, PhD. thesis, Department of Mechanical Engineering, University of Bristol, 1978. [9] Wilcox P., Lamb wave inspection of large structures using permanently attached transducers, Ph.D. thesis, Department of Mechanical Engineering, Imperial College of Science, 1998. [10] Boavids J., Oliveira A., Berberan A., Dam monitoring using combined terrestrial imaging systems, 13th Symposium on Deformation Measurement Analysis, Lisbon, 1-12, 2008. [11] Wilde K., Modal diagnostics of civil engineering structures, Wydawnictwa Politechniki Gdańskiej, 2008. [12] Rucka M., Wilde K., Application of continuous wavelet transform in vibration based damage detection method for beam and plates. Journal of Sound and Vibration 297, 2006, 536-550. [13] Mulherin M., Atmospheric icing and communication tower failure in the United States, Cold regions science and technology, 27, 1998, 91-104. [14] Paczkowska T., Paczkowski W., Aspekty budowlane katastrofy energetycznej w rejonie szczecińskim, Awarie Budowlane, XXIV Konferencja Naukowo-Techniczna Szczecin-Międzyzdroje, 2009, 151- 176 (in Polish). [15] Maguire J., Residual life assessment of electricity pylons – a case study, Key Engineering Materials, 413414, 2009, 219-228.

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