Acta Energetica Power Engineering Quarterly 1/10 (March 2012) by ENERGA SA

POWER ENGINEERING QUARTERLY

Special Issue 01/2012 number 10/year 4

Smart Grid

Patronage Publisher

ENERGA SA

Politechnika Gdańska

Patronage

ENERGA SA

Academic Consultants

Janusz Białek / Mieczysław Brdyś / Mirosław Czapiewski Antoni Dmowski / Michał Dudziak / Istvan Erlich / Andrzej Graczyk Piotr Kacejko / Tadeusz Kaczorek / Marian Kazimierowski / Jan Kiciński Kwang Y. Lee / Zbigniew Lubośny / Jan Machowski / Om Malik Jovica Milanovic / Jan Popczyk / Zbigniew Szczerba / Marcin Szpak G. Kumar Venayagamoorthy / Jacek Wańkowicz

Reviewers

Stanisław Czapp / Andrzej Graczyk / Piotr Kacejko / Jan Kiciński Zbigniew Lubośny / Jan Machowski / Józef Paska / Jan Popczyk Desire Dauphin Rasolomampionona / Sylwester Robak Marian Sobierajski / Paweł Sowa / Zbigniew Szczerba / Artur Wilczyński

Editor-in-Chief

Zbigniew Lubośny

Vice Editor-in-Chief

Rafał Hyrzyński

Copy Editors

Katarzyna Żelazek / Bernard Jackson

Topic Editors

Michał Karcz / Jacek Klucznik / Marcin Lemański / Paweł Szawłowski

Statistical Editor

Sebastian Nojek

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Information about the original version

The paper edition of Acta Energetica is the original version of the journal. The journal is also available on the website www.actaenergetica.org The journal is indexed in Polish Technical Journal Contents BazTech baztech.icm.edu.pl

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featuring information for authors We accept only the articles that have never been published before. Each text sent to Acta Energetica is subject to scientific review. The editorial meeting decides when the texts are published. We do not send the texts backs to the authors.

Please send the materials, which must consist of the entire package of five components (article, abstract, bibliographical note, Zbigniew photograph ofLubośny the author, graphic files used in the article) electronically to the following address: redakcja@actaenergetica.org From the editor

NOTE! E-mail content must include contact data: given name and surname, degree, telephone number (stationary and mobile) and e-mail address. 1. ARTICLE

Marek Laskowski | Michał Zabielski • Text length. Not more than 12 standard pages (characters: size 12, interlines: 1.5), 1 column. Introduction toand strategic research program “Advanced Technologies of Energy Generation” • Format. WORD file PDF as a must. • Writingwhich formulas.the Please follow Grid the punctuation standards carefully. We use the “×” sign to indicate multiplication. Please write under Smart concept is developed any formulas using Microsoft Equation 3.0 editor.

Rafał Magulski e ⎛ I1 0,95 λ × ⎜ Examples:and legal A3 = conditions A3 L × 1 = of 0,1Smart × = 0,deployment 19 K = 1 + Formal Grid 1 + e ⎜⎝ I Σ 0,5 λn

2 2 ⎞ ⎡ h=n ⎛ I h ⎞ q ⎤ ⎟⎟ × ⎢∑ ⎜⎜ ⎟⎟ xh ⎥ ⎥⎦ ⎠ ⎢⎣ h=2 ⎝ I1 ⎠

Footnotes. At the bottom of each page.

18 24

Aleksander Babś | Maciej Makowski Examples: Market aspects of smart power grids development Journal of laws No 203 pos. 1684 of 17 October 2005.

The examples are dealt with in the book: Fiedor B., Graczyk A., Jakubczyk Z., Rynek pozwoleń na emisję zanieczyszczeń na przykładzie SO2 w energetyce polskiej [Pollution Emission Allowances Market in Polish Power Engineering on the Example of SO2], Sławomir | i Środowisko, Adam Babś | Krzysztof Madajewski WydawnictwoNoske Ekonomia Białystok 2002, pp. 39–42.

A visionAt ofthe Smart Grid Literature. end of the text.deployment at ENERGA-OPERATOR SA Examples: 1. Larsen E.V., Swann D.A., Applying Power System Stabilizer, IEEE Trans. Power Appar. Syst., vol. 100, 1981, pp. 3017–3046.

Rafał Czyżewski | Adam Babś | Krzysztof Madajewski

2.Madajewski K., Sobczak B., Trębski R., Praca ograniczników w układach generatorów synchronicznych w warunkach Smart Grids – selected objectives and directions ofregulacji distribution system operator actions niskich napięć w systemie elektroenergetycznym, materiały konferencyjne APE ’07, Gdańsk 2007.

Adam Babś | Krzysztof Madajewski | Tomasz Ogryczak • Text length. Not more than 1100 characters (without spaces). Sławomir Noske | PDF Grzegorz Widelski • Format. WORD file and as a must. “The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA 3. BIBLIOGRAPHICAL NOTE

2. ABSTRACT

• Text length. Ca 900 characters (without spaces). • Format. WORD file and PDF as a must.

Andrzej Kąkol | Ksawery Opala 4. PHOTOGRAPH

Selected results of simulation studies in “The Smart Peninsula” project

Stanisław Kubacki | Jacek Świderski | Marcin Tarasiuk 5. GRAPHIC FILES Comprehensive automation and monitoring of MV grids thescreenshots key element • Format. Vector graphics (ai, eps formats), Bitmap graphics (photographs, at least as 300 dpi, in the maximum possible resolution are allowed. Vector files should not be converted into bitmap files. The editorial office does not accept files sent in cdr of improvement of energy supply reliability and continuity

• Format. Black and white or colour photo, jpg or tiff, 300 dpi, at least in the size sufficient to be published in print, at least 2.5 cm/3.5 cm.

(Corel Draw) format. • Mathematical equations. It should be possible to convert formulas to vectorial form. Using Microsoft Equation 3.0 is recommended

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Introduction to strategic research program “Advanced Technologies of Energy Generation” under which the Smart Grid concept is developed

authors | biographies

Marek Laskowski

Michał Zabielski

Manager of ENERGA SA Investment Project Department. Graduated from the Faculty of Electrical and Control Engineering at Gdańsk University of Technology and then completed postgraduate studies in Project Management at SGH Warsaw School of Economics. Professionally involved with the power sector since 2002, first in Elbląskie Zakłady Energe¬tyczne SA, since January 2005 in the newly established organisation of Koncern Energetyczny ENERGA SA. He implemented projects to improve customer service standards, was responsible for development of billing systems and their adjustment to the applicable legal regulations. He participated in the works of a team dedicated to electricity distribution and trade decoupling. Since 2008 at ENERGA SA he has managed and coordinated key capex projects implemented by ENERGA SA. group companies. Now manages two key projects, incl. ENERGA SA’s first innovative projects implemented jointly with The Polish Academy of Sciences Robert Szewalski Institute of Fluid-Flow Machinery.

Graduated from the Faculty of Management and Economics of Gdańsk University of Technology (2008). Has completed postgraduate studies in Project Management at the University of Gdańsk (2011). A certified programme and project manager. Involved with the power sector since 2008.

Gdańsk | Poland

Special Issue – Smart Grid

Gdańsk | Poland

Marek Laskowski | Michał Zabielski

Introduction to strategic research program “Advanced Technologies of Energy Generation” under which the Smart Grid concept is developed 1. BACKGROUND OF JOINING RESEARCH TASK 4. (PROJECT) The key objective of the Polish science development is to utilise its products in raising Poland’s civilisation level, by way of, inter alia, wider implementation of R&D results in the education, economy, and culture. The national science’s particularly relevant task is its active participation in narrowing the civilisation gap between Poland and countries of highly developed economies, and improvement of the Polish society’s quality of live in line with the sustainable development principle. Given the above and having adopted the development of a knowledge-based economy as one of the strategic objectives of the state’s scientific, scientific-technical, and innovative policy, The Ministry of Science and Higher Education published in 2008 a so called National Plan of Research and Development, updated in August 2011 as the National Programme. The document is an instrument that facilitates implementation of the state’s scientific, scientific-technical, and innovative policy adjusted to European and global standards. It allows directing the stream of R&D funding to the areas and scientific disciplines with the strongest impact on the country’s social and economic development. Program implementation should contribute to increased research effects in new technological solutions, the number of patents, and innovative economy technology. Achieving the foregoing goals requires concentration of scientific communities’ involvement and the state budget’s funding of a limited number of separated priority areas. The National Research Programme covers seven strategic and interdisciplinary R&D directions identified based on expert consultancy of science and industry representatives. As the executive body of The National Research Programme the Ministry of Science and Higher Education has appointed The NCBiR National Centre for Research and Development. Based on the priority areas identified so-called strategic R&D programmes have been formulated.

They feature a mid-term implementation period and are subject to modification resulting from changing conditions, tasks, and needs of the economy and society. In the framework of strategic research and development programmes research tasks are specified. These are set by The National Centre for Research and Development, which then selects contractors by way of competition proceedings. In the figure below a diagram representation is shown of subsequent steps in defining strategic R&D programmes. The Council of Ministers on a proposal from the Minister of Science and Higher Education establishes

The NCBiR National Centre for Research and Development The NCBiR Steering Committee present

The National Research programme in terms of R&D directions

Strategic R&D programmes

Research Task 1

Long-term objectives

Mid-term objectives

Research Task n

Research Task 2

Fig. 1. Development principles of strategic R&D directions and programmes

Since the Polish power sector should undergo longterm transformation in order to become a sustainable and low carbon, environmentally friendly system benefiting from a differentiated mix of energy resources system, while increasing energy efficiency, the area has been classified for inclusion to The National Research Programme. The national power sector infrastructure in need of modernisation and inefficient, dependency on externally supplies of fuel and energy, the sector’s adverse environ-

Abstract The paper presents a brief introduction to strategic programme “Advanced Technologies of Energy Generation”, under which Research Task 4. “Development of Integrated technologies for Production of Fuels and Energy from Biomass,

Agricultural Waste and Other Materials” is implemented. The context justifies joining the task, its main objectives, management structure, and entities involved. Also justified is the inclusion of Smart Grid concept to the project scope.

Special Issue – Smart Grid

Marek Laskowski, ENERGA SA | Michał Zabielski, ENERGA SA

mental impact, and Poland’s obligations following from the European Union’s adoption of the “Climate-Energy Package are factors which clearly indicate the need to implement a number of significant technological changes in the structure of energy generation, transmission, efficient distribution, and storage. It should be underlined that the development of modern energy generation and management technologies is of key relevance for the process of transformation towards a green economy, thus contributing to accomplishment of the objectives defined in the “Europe 2000” strategy. The indicated documents assume the accomplishment of energy supply security subject to compliance with environmental protection requirements, and the development of low-emission technologies that enable the fulfilment of the of “3x20 Package” objectives. According to the content of the package contained in the European Committee Communication of 10 January 2007, which assumes that by 2020 the EU’s overall balance shall feature: 1. energy efficiency improved by 20% 2. renewable energy share increased by 20% 3. CO2 emission reduced by 20%. R&D in the power sector must contribute to the implementation of the “Polish Energy Policy until 2030” programme adopted by the Council of Ministers, as well as to the fulfilment of the objectives of the European Union’s climate policy [1], [2]. On 4 June 2009 The NCBiR National Centre for Research and Development, as the executive body of The National Research Programme announced a contest for the strategic R&D programme entitled “Advanced technologies for obtaining energy”. The strategic programme objective is to develop technological solutions, the implementation of which shall contribute to the fulfilment of the assumptions of the European Union’s “3x20 Package”. This initiative consists of the following four research tasks defined by the NCBiR Centre: 1. Development of a technology for high-efficiency “zeroemission” carbon sets integrated with CO2 capture from fumes. 2. Development of an oxygen combustion technology for dust and fluid boilers integrated with CO2 capture. 3. Development of a coal gasification technology for high-efficiency production of fuels and electricity. 4. “Development of integrated technologies for production of fuels and energy from biomass, agricultural waste and other materials” In response to the competition proceedings The Robert Szewalski Institute of Fluid-Flow Machinery of The Polish Academy of Sciences approached ENERGY S.A. with a proposal to set up a scientific/ industrial consortium that would submit an offer for Research Task 4, i.e. “Development of integrated technologies for production of fuels and energy from biomass, agricultural waste and other materials”. The project implementation was found to be in line with Objective 3 of the ENERGA Capital Group Strategy, i.e. “Accomplishment of the leadership

Special Issue – Smart Grid

in development of distributed, and renewable in particular, energy generation sources”, and with the need to develop Smart Grids capable of interaction with distributed electricity sources. The consortium was established on 19 August 2009 by way of an agreement, under which the Institute of Fluid-Flow Machinery was appointed the organisation’s leader, and ENERGA SA its industrial partner co-funding a portion of the research, and vitally interested in its result with a view to its implementation in ENERGA Capital Group companies. The consortium filed its offer with the NCBiR Centre in September 2009 and won the competition, and so, therefore, it undertook the fulfilment of Research Task 4.

2. RESEARCH TASK 4. OBJECTIVES The main objective of Research task 4 consists in: 1. Development of innovative electricity and heat cogeneration technologies with concurrent bio fuel production 2. Development of a series of distributed power generation system types. 3. Development and execution of pilot demonstration systems as the basis for future implementation of modern technologies. 4. Development of a concept of distributed generation integration with power grid 5. Development of a concept of autonomous power region. The project was launched on 28 May 2010, and its completion is scheduled for 31 May 2015. The total project budget amounts to PLN 110 million, PLN 70 million out of which is the NCBiR’s subsidy, and PLN 40 million has been contributed by consortium members.

3. PROJECT SCOPE Research Task 4. consists of the eight thematic blocks presented in the figure below, divided into 56 detailed research stages. A portion of the work, including the stage

Research Task 4. Block 1

Polygeneration power plants

Block 2

Home micro-gas plants

Block 3

Biomass thermal gasifier systems

Block 4

Gas and liquid fuels conversion-based production systems

Block 5

Biogas cleansing and refining

Block 6

Fuel cell-based cogeneration systems

Block 7

New process and material technologies testing

Block 8

The integration of distributed generation of electricity grid

Fig. 2. Thematic blocks in Research Task 4.

Introduction to strategic research program “Advanced Technologies of Energy Generation” under which the Smart Grid concept is developed

of Smart Grid concept development in the eighth block, is managed by ENERGA SA, while the Institute of FluidFlow Machinery is in charge of the rest of the scope.

is one of the largest and most thriving innovation centres in Poland. It is financed by the State Treasury and with European Union aid funds [3].

Each thematic block stage shall be implemented in the form of basic research, industrial research, and development works. The above formula is justified by the R&D nature of the project, and results from rules stipulated in the contract for Research Task 4. execution by and between the NCBiR Centre and the consortium.

The Robert Szewalski Institute of Fluid-Flow Machinery of The Polish Academy of Sciences The Institute of Fluid-Flow Machinery, leader of the consortium implementing Research Task 4., was established as a R&D unit in 1956 for scientific research in the area of operating basics, engineering, construction, and development of the machinery for energy conversion in flows. The Institute conducts experiments in the following four areas: renewable energy sources (RES), small scale cogeneration systems, fluid mechanics, multiphase flows, thermodynamics and heat exchange, plasma physics, laser technology, machinery mechanics, tribology, and power machinery diagnostics. The Institute staff consists of 170 employees, including 80 researchers. The Institute is authorised to grant doctor and habilitated doctor degrees of engineering in the disciplines such as: mechanics and machinery construction and operation. The institute organisation consists of four centres divided into fifteen research departments. Besides research the Institute provides consultancy services in engineering matters, including turbine related issues. The effects of the Institute’s research are published by its own publishing house, IMP PAN [4].

4. PARTIES INVOLVED IN THE PROJECT IMPLEMENTATION The approach path to the Research Task 4. implementation required involvement of numerous parties. Strategic areas in knowledge-based economy development in the form of a research programme had been set by the Ministry of Science and Higher Education of the Republic of Poland, while the program executive body is the National Centre for Research and Development. After the nationwide competition’s announcement and resolution the project has been implemented by scientific/ industrial consortium of The Institute of Fluid-Flow Machinery and ENERGA SA, with the contribution of partners.

The NCBiR National Centre for Research and Development It is an executive agency of the Minister of Science and Higher Education within the meaning of the Act of 27 August 2009 on the Public Finance, appointed to carry out tasks in the area of the state’s scientific, scientific-technical, and innovative policy. At the time of its establishment, i.e. in the summer of 2007, it was the first organization of its kind in the country, appointed as a platform for exchange of knowledge, experience, and capital at the interface between science and business. The NCBiR mission is to support national research units and enterprises in their efforts to extend their ability to create and use solutions developed as a result of scientific research in order to intensify economic development and to the benefit of society. The centre’s main tasks include the management and implementation of strategic R&D programmes, which, upon their commercialisation, will directly translate to the development of Poland’s innovativeness. It is an executive body of the National Research Programme, including the strategic R&D programme entitled “Advanced technologies of energy production”, actively participating in development of initiatives that contribute to the implementation of assumptions of the climate – energy package, and the “Polish Energy policy until 2030.” Now the agency operates pursuant to the Act of 30 April 2010 on the National R&D Centre. On 1 September 2011 the NCBiR Centre extended the scope of its mandate by new initiatives and capabilities, having taken over from the Ministry of Science and Higher Education the role of intermediary institution in the following Operational Programmes: Human Capital, Innovative Economy, and Infrastructure & Environment. It

ENERGA Capital Group It is an integrated energy company that generates, trades, and distributes electricity and heat. The Group’s electricity output amounts to over 4.6 TWh, out of which 1.6 TWh is generated from renewable sources. It generates electricity in 53 plants, mainly in coal-fired plant in Ostrołęka, cogeneration plants in Elbląg and Kalisz, a hydro plant in Włocławek, and numerous small hydro plants. The Group’s installed power currently amounts to around 1.2 GW, including 0.3 GW in renewable sources. In addition, numerous wind plants, small hydro plants and bio gas plants, with which the Group cooperates, are connected to the grid. ENERGA Capital Group supplies electricity to 2.5 million households and over 300,000 companies, which accounts for around a 16% share in the electricity sales market, and the volume in the range of 18.5 TWh. Over 15% of the energy supplied to the Group’s customers has been generated in renewable sources. The group is an operator of a power distribution system that covers 1/4 of Poland’s territory. It operates power lines of the total length of over 188,000 km to transmit over 19 TWh yearly, which accounts for around a 16% market share. The Group employs over 12.6 thousand employees which makes it one of the largest employers in the country.

Special Issue – Smart Grid

Marek Laskowski, ENERGA SA | Michał Zabielski, ENERGA SA

ENERGA SA Is ENERGA Capital Group’s dominant and managing company. It sets the Group’s development directions and investment goals provided for in the Group Development Strategy for 2009-2015. It integrates electricity and heat generation, distribution, and trade companies under one brand. It is a member of the research consortium and ENERGA Capital Group’s representative that co-finances Research Task 4. and carries out some research stages on its own. ENERGA-OPERATOR SA It is one of ENERGA Capital Group’s key assets, the third largest distribution grid operator (DSO) in the country in terms of the transmitted electricity volume. Its fixed assets are valued at approx. PLN 6.7 billion. It operates 6,200 km of high voltage lines, 64,500 km of medium voltage lines, and 82,000 km of low voltage lines to supply approx. 2.8 million consumers. It actively participates in programmes aimed at grid upgrade and efficiency improvement. Now it carries out works related to implementation of a smart metering system (AMI) prepared for integration with future Smart Grid solutions (Smart Grid Ready). Ultimately, under the AMI System deployment programme approx. 3.1 million meters will be replaced. The company has joined the European association EDSO for Smart Grids. This organization, co-working

with the European Union’s agencies, creates new standards for development and management, and participates in drafting legal regulations for smart distribution grids. The purpose of ENERGA-OPERATOR SA’s membership in the association is to strengthen cooperation on a European level with leading distribution companies (DSOs) in order to exchange experiences in Smart Grid development and deployment. The company also belongs to the structures of the international organisation PRIME Alliance that brings together major participants of the smart power grid market with a view to the development of a global standard for communication of devices and development of AMI – PRIME PLC systems. In connection with Research Task 4. implementation and on the basis of ENERGA-OPERATOR SA’s distribution grids a Smart Grid development concept will be conceived providing for a pilot project in a selected location, in the context of cooperation with distributed energy sources and in variable conditions [5].

5. PROJECT ORGANISATION Management of the project is organised in a structure whereby the Institute of Fluid-Flow Machinery is leader and consortium representative in relations with the NCBiR Centre, and ENERGA SA is an industrial partner. In the framework of internal cooperation, agreements have been concluded by and between research and in-

CONSORTIUM LEADER THE ISNTITUTE OF FLUID-FLOW MACHINERY Coordination of consortium members’ and cooperating entities’ interactions

MANAGING TEAM • Monitoring and supervision of timely completion of the research task’s individual stages • Setting schedule of consortium activities • Substantive and formal acceptance of works • STEERING COMMITTE

MANAGING TEAM FINANCIAL & ACCOUNTING SERVICES • Supervision and settlement of accounts for expenditure of funds received by the consortium • Reporting, accounting, tender organisation

LOCAL BRANCHES, CO-CONTRACTOR OFFICES RESEARCH TASK MANAGER

THEMATIC BLOCK MANAGERS COORDINATOR OF INDUSTRIAL/ DEVELOPMENT OBJECTIVES

LOCAL BRANCHES, CO-CONTRACTOR OFFICES

CONSORTIUM MEMBER ENERGA SA Coordination of industrial partners’ contributions Analysis of implementation opportunities and business products

Special Issue – Smart Grid

Fig. 3. Research Task 4. management structure

Introduction to strategic research program “Advanced Technologies of Energy Generation” under which the Smart Grid concept is developed

dustrial entities that declared their will to participate in the project. ENERGA SA representatives act as manger of Part 4 of Research Task, individual stage coordinators, and Coordination Office Division.

6. SMART GRID IN THE PROJECT For Poland the implementation of the strategic research programme entitled “Advanced Technologies of Energy Production” is undoubtedly a challenge and an economic development opportunity. The renewable sources – based development of the power sector requires however many changes not only in the applicable legal regulations, but also the development of a concept enabling smart management of electricity generated, inter alia, in these units. Smart Grids herein referred to are a comprehensive power solution that allows for interconnection, mutual communication and optimum control of so far dispersed elements of the power infrastructure – on the sides of producers and consumers alike, enabling energy consumption opti-

2. The European Commission Communication that clearly explains the need to develop and implement technical standards and legal regulations in the Member States with regard to Smart Grids as one of the main factors of the development of a low-emission and efficient power system with increased share of RES and transportation vehicles’ electrification. 3. Limited implementation of projects with regard to comprehensive Smart Grid solutions, and therefore the need to develop an engineering and business concept for Smart Grid taking into account the possibility of operation and testing in a selected pilot area, in connection with assumed increase in the number of distributed sources. 4. The need to build consumer awareness that the Smart Grid deployment should stimulate changes in their habits, intensify their proactive attitudes and adjustment to new energy consumption standards, for transition to an efficiency-based business model. A perfect example is the Japanese approach that puts fundamental emphasis on the otherwise often Fig. 4. Infrastructure in the service of social life according to Hitachi [7]

misation and energy services quality improvement. Smart Grid solutions cover the area of electrical grids, ICT networks, and the energy market. They pertain to distribution automation, smart metering, demand side and supply side management, renewable energy resources management including storage [6]. The contentrelated scope of information that describes Smart Grid in detail will be presented in the other articles in this publication. Premises for the Smart Grid concept’s inclusion to the subject scope of Research Task 4. have been justified in a broader perspective in: 1. Requirements of the “Climate – Energy Package” which Poland has undertaken to fulfil, in particular in the aspect related to energy efficiency improvement and increased share of renewable energy sources in the overall mix that directly translates to the “Polish Energy policy until 2030”.

neglected society’s role in the process of smart solutions’ development. The Smart Grid deployment brings about many benefits for end consumers of energy, the environment, as well as the power system. Since there are no Smart Grid comprehensive solutions and implementations, in the subject scope of Research Task 4. a stage has been included entitled “Development of a Smart Grid concept and technical and business model on the medium voltage (MV) level in the context of cooperation of local energy sources in the conditions of the grid’s normal operation and fault (possible island operation case)”. The study consists of the following three thematic blocks [8]: 1. Smart Grid deployment and operation concept 2. Simulation studies of grid operation and grid control algorithms in a selected pilot location – the Hel Peninsula

Special Issue – Smart Grid

Marek Laskowski, ENERGA SA | Michał Zabielski, ENERGA SA

3. Feasibility study of the project implementation in a selected pilot location – the Hel Peninsula 4. Road map for the project implementation in a selected location – the Hel Peninsula. As a result of the project works and conceived concept it was decided to issue this publication that introduces Smart Grid issues in the areas such as: 1. “Smart Grids – selected objectives and directions of distribution system operator actions” by Rafał Czyżewski, Adam Babś, and Krzysztof Madajewski 2. Pilot project of “The Smart Peninsula” Smart Grid deployment at ENERGA-OPERATOR SA” by Adam Babś, Krzysztof Madajewski, Tomasz Ogryczak, Sławomir Noske, and Grzegorz Widelski 3. “Comprehensive automation and monitoring of MV grids as the key element of improvement of energy

supply reliability and continuity” by Jacek Świderski and Marcin Tarasiuk 4. «Selected results of simulation studies in «The Smart Peninsula» project» by Andrzej Kąkola and Ksawery Opala 5. “Formal and legal conditions of Smart Grid deployment» by Rafał Magulski 6. “A vision of Smart Grids deployment at ENERGA-OPERATOR SA» by: Sławomir Noske, Adam Babś, Krzysztof Madajewski 7. “Market aspects of smart power grids development» by Aleksander Babś and Maciej Makowski. Enjoy reading!

References 1. “Krajowy Program Badań Naukowych i Prac Rozwojowych” [The National R&D Programme], The Ministry of Science and Higher Education, 2008. 2. “Krajowy Program Badań. Założenia polityki naukowo-technicznej i innowacyjnej państwa” [The National Research Programme. Assumptions for the State’s Scientific-Technical and Innovative Policy], Attachment to the Resolution 164/2011 of the Council of Ministers of 16 August 2011. 3. http://www.ncbir.pl/. 4. http://www.imp.gda.pl/. 5. http://www.grupaenerga.pl. 6. Szyjko C., Technologie smart w służbie polskiej energetyki [Smart technologies in the service of the Polish power sector], Czysta Energia, No. 6/2011. 7. Presentation “Inteligentne Miasto według firmy Hitachi” [Smart City according to Hitachi], 2012. 8. “Koncepcja oraz model techniczny i biznesowy sieci inteligentnej (Smart Grid) na poziomie średniego napięcia (SN) w kontekście współpracy lokalnych źródeł energii w sytuacjach normalnej pracy oraz awarii sieci (możliwość pracy wyspowej)” [“A Smart Grid concept and technical and business model on the medium voltage (MV) level in the context of cooperation of local energy sources in the conditions of the grid’s normal operation and fault (possible island operation case)”], ENERGA-OPERATOR SA, 2012.

Special Issue – Smart Grid

Formal and legal conditions of Smart Grid deployment

authors | biographies

Rafał Magulski Gdańsk | Poland

Graduated in Management and Marketing from the Faculty of Management and Economics of the University of Gdańsk (1998). An analytical specialist at the System Strategy and Development department of the Institute of Power Engineering, Gdańsk Division. His professional interests include market issues in the power sector and pre-design studies on power system development.

Special Issue – Smart Grid

Rafał Magulski

Formal and legal conditions of Smart Grid deployment 1. LAW AND POLICY OF THE EUROPEAN UNION Regulations contained in EU directives are binding on the Member States regarding the result to be achieved, whilst leaving national authorities of the Member State the choice of form and legal measures. For this reason EU Directives must be implemented into the Member State legislations to achieve the legal effect they provide for, and consequently they have an impact on the current state of national legal regulations and the future directions of their amendments, also as regards the capacity to implement Smart Grid solutions. Directive 2005/89/EC concerns the measures to safeguard security of electricity supply and infrastructure investment. A high level electricity supply security is to be secured by means of the development of generation and transmission and distribution infrastructure (including the provision of stable conditions for investment) and the development of the energy market. The task of the Member States is to define the roles and responsibilities of key energy market players and competent state authorities (including the scope of regulatory powers and controls), and to publicise information on this topic. According to the Directive, the Member States and/ or competent authorities shall ensure that transmission system operators and, where appropriate, also distribution system operators, shall identify and implement the objectives in terms of supply quality and grid operation security. These objectives are subject to approval by the Member States and/or competent authorities, and their implementation is monitored by them. The Directive points to the promotion of advanced metering systems as one of the steps that the Community countries can take in order to balance supply and demand for energy. Smart metering is seen as an instrument that can contribute to reducing demand for electricity, and, consequently, can influence increased energy security.

The purpose of Directive 2006/32/EC is the economically feasible improvement of the efficiency of final energy use in EU countries, provision of additional incentives to reduce electricity consumption, and stimulation of the development of services in the energy sector. The Directive sets an indicative target – 9% energy savings by 2016. The act provides for the option to launch national public aid programs, to support activities aiming at energy efficiency. These activities include advanced metering systems, and billing and invoicing systems that provide customers with information on energy consumption and prices. The Directive obliges Member States to implement regulations to enable the use of individual metering devices that allow obtaining information about the current energy consumption and actual time of its use. Where it is technically feasible, these devices should be on the market at cost effective prices, and the incurred expenditures should be proportionate to the achieved energy efficiency improvement. These activities are intended to enable customers to adjust the current levels of their energy consumption, taking into account the current electricity prices. With a view to improving the operations and integration of competitive energy markets in the Community, Directive 2009/72/EC lays down common rules for the generation, transmission, distribution and supply of electricity together with consumer protection regulations. Pursuant to the Directive of a distribution system operator shall be responsible for ensuring the system’s long term ability to meet reasonable demand for the distribution of electricity, for economically feasible operation, maintenance, and extension of the secure, reliable, and efficient electricity distribution system in its area, with due regard for the environment and energy efficiency.

Abstract This article presents an overview of the formal and legal issues arising from EU policies and national regulations affecting the capacity to implement Smart Grid solutions. EU legislation currently imposes on the Member States no obligation to apply any mechanisms to support implementation of Smart Grid solutions in the power sector. Directives call for the introduction of such national regulations that promote improved security and reliability of energy supply, development and integration of renewable and distributed energy resources with the power system, and development of the energy mar-

ket to allow customers to respond to market incentives and to rationally change their behaviours as regards energy use. Not all of the obligations and recommendations have been fully transferred into the national legislation. However, directions of the Polish energy policy are in line with European trends and clearly indicate Smart Grids as one of the remedies to the challenges that the National Power System will have to cope with in the long term. Therefore, some significant legislative changes regarding the power sector should be expected in the near future.

Special Issue – Smart Grid

Rafał Magulski, Institute of Power Engineering, Gdańsk Division

The Directive’s preamble contains a recommendation to EU Member States to encourage their distribution grids’ modernisation, for example, by the deployment of Smart Grids, which should be so procured as to stimulate the development of decentralized electricity generation and improve energy efficiency. The Directive requires that in planning the distribution grid extension, the distribution system operator shall take account of the measures related to energy efficiency / demand-side management or distributed generation, which can replace the need to modernize and/or to increase the capacity. Annex I to the Directive provides guidance to the Member States with regard to activities related to the deployment of smart metering systems. By 3 September 2012 Member States should carry out an economic analysis of the deployment of a smart metering system, taking into account the costs and benefits from the market and customer standpoints. This analysis should indicate the optimal system for each Member State, and should set a deployment timetable, assuming that it should be completed in ten years. In the case of positive analysis results the deployment of smart metering should cover at least 80% of recipients. The Member States should ensure interoperability of measuring systems by defining relevant standards and identifying best practices. Directive 2009/28/EC establishes a common framework for the Member States in promoting the use of energy from renewable sources, and sets mandatory national targets for the share of energy from renewable sources in the gross final consumption of energy in general. The Directive requires the Member States to take appropriate steps to procure the infrastructure for power transmission and distribution grid, Smart Grids, storage facilities, and power system in order to ensure secure operation of the power system while adapting it to the further development of electricity generation from renewable energy sources.

2. NATIONAL ENERGY AND REGULATORY POLICY As of now not all Directives presented in the first chapter have been reflected in the legislation in force in Poland. Catalogued below are strategic documents and legal acts that condition the distribution system operators’ capacity to implement Smart Grid solutions.

2.1. The Polish Energy Policy until 2030 “The Polish Energy Policy until 2030” (PEP 2030) adopted by the Council of Ministers in September 2010 sets six basic directions of development of the Polish energy sector. For each of these directions’ specific objectives have been formulated, as well as implementation activities and the manner of their execution, and the deadlines and entities in charge have been set. These basic directions of the Polish energy sector development include energy efficiency improvement, increase in fuel and energy supply security, and renewable energy sources development.

Special Issue – Smart Grid

The following objectives have been adopted as crucial for improving energy efficiency: maintaining net-zero economic growth, i.e. the Polish economy’s growth with no increased demand for primary energy, and consistent reduction of the Polish economy’s energy intensity to the EU-15 level. The specific goals thereby envisaged include the following: • reduction of the transmission and distribution grid losses rate by upgrading the existing and building new grids, replacement of low efficiency transformers and development of distributed generation • flattening of the annual electricity demand curve that leads to reduced total cost of meeting the demand for electricity. The implementation activities include: –– gradual introduction of the obligation to use electronic meters that allow transmission of price signals to energy consumers –– provision of the applicability of a system of incentives for electricity consumption rationalisation through distribution tariffs (e.g. multi-zone tariffs) –– application of Demand Side Management techniques, stimulated by such measures as diurnal variation of distribution rates and electricity prices based on reference prices, resulting from introduction of the present day market, and transmission of price signals to customers equipped with smart meters. The programme of implementation activities planned until 2012 provides also for the introduction of a digital communication standard to provide conditions for development of a single national radio communication system for the power sector that ensures voice communication and data transfer implementation, both in normal and in crisis situations. The Energy Policy’s primary objective in the area of fuel and energy supply security is to provide continuous coverage of the demand for energy taking into account the maximum possible use of national resources and environment friendly technologies. The specific goals envisaged include modernization and expansion of distribution grids, which allows improving the reliability of power supply, development of distributed generation taking advantage of local energy sources, upgrading transmission and distribution grids to enable reducing emergency supply interruption durations by 2030 to 50% of the duration in 2005. Planned activities include introducing an element of quality to the transmission and distribution tariffs. Power system operators will be entitled to a bonus for lower failure rates and maintaining them at the grid type specific levels required by the President of the ERO. The document assumes that the development of renewable energy generation is essential for the achievement of the Energy Policy’s fundamental objectives. For this reason the document considers the implementation of solutions, particularly with the use of innovative technologies, which ensure the stability of power system operation, as important.

Formal and legal conditions of Smart Grid deployment

2.2. Strategy for Energy Security and Environment. Perspective 2020 Ministry of Environment and Ministry of Economy have drafted the strategy “Energy Security and Environment”. The strategy states that in the national energy system the benefits offered by renewables must be realized to increase energy security in those areas where the power sector development could face severe restrictions. According to the authors it should, however, be noted that the development of renewable source-based distributed generation would require adjustment to the new conditions of the transmission and distribution grids, operating procedures, protections, etc. The strategy sets benchmarks to measure the degree of fulfilment of its objectives. The following indicators serve to ensure the national economy’s secure and competitive energy supply:

Indicator

Baseline in 2009

Value expected in 2020

SAIDI index

341.6 mins

200 mins

SAIFI index

4.0

less than 1.5

–

80%

Number of consumers with smart energy meters

2.3. Draft “National Spatial Planning Concept 2030” The “National Spatial Planning Concept 2030” has been drafted at the Ministry of Regional Development and is currently undergoing public consultation. One of the Concept’s objectives is to increase the spatial structure’s resilience to natural hazards and loss of energy security. For this reason the energy infrastructure development in 2030 perspective will have to respond to some fundamental challenges: • CO2 emission reduction to a level agreed in the European Union • extension of low-voltage transmission grid, which is necessary for connecting new generation sources, including renewables, and for power output from them • improved efficiency of electricity transmission, supply and consumption through the development of Smart Grids. Another goal considered in the Concept is the extension of interconnections within the country, leading to improved security of supply of large cities and the north of Polish. The Concept’s authors envisage that further development of power grids will take place through the development and implementation of Smart Grid technologies, including IT technologies. Generators and distributors will begin adjusting their equipment to grid control and to grid regulation and protection in order to increase the reliability and quality of supply and to reduce the environmental impact

of energy processes. Smart energy meters with remote data transfer will become widespread among consumers.

2.4. The Energy Efficiency Act The Energy Efficiency Act1 also fulfils the provisions of Directive 2006/32/EC. The Act sets a national target for economic energy management as the final energy savings by 2016 of not less than 9% of the average domestic consumption of this energy in a year. The Act establishes a legal framework for actions to improve the economy’s energy efficiency. It introduces a mechanism of support in the form of a white certificate scheme. The system will be based on the already existing schemes that support cogeneration and renewable energy sources. Energy companies that sell electricity, heat, and/or natural gas to end users will be required to obtain and submit energy efficiency certificates to the President of ERO for redemption (in a number pro rata to the volume of sales) or pay a substitute fee. These certificates will be issued by the President of ERO at requests of entities that have implemented solutions to improve energy efficiency. In order to facilitate selecting solutions of energy efficiency improvement, which can be awarded with the energy efficiency certificates, the President of ERO will announce and organize tenders, separately for each category of solutions: • energy saving by end users • energy saving by auxiliary equipment (in electricity and/or heat generation plants) • reducing electricity, heat, and natural gas losses in transmission and/ or distribution (in particular reduction of reactive power flows, grid losses in line strings and losses in transformers). 2.5. The Energy Law The Energy Law of 1997 is the basic legal act setting up the rules of the state energy policy, and the terms and conditions of supply and use of electricity, and of the operations of energy companies. None of the existing provisions of the Act include a direct regulation of the use of Smart Grid solutions. The following provisions may have an indirect impact: 1. Responsibilities of distribution grid operators with regard to: • management of the distribution grid operations in an efficient manner while maintaining the required reliability and quality of electricity supply in the 110 kV grid • operation, maintenance and repair of the distribution grid in order to ensure the distribution system’s reliable operability • grid development planning with consideration of projects related to energy efficiency and/or electricity demand-side management • assurance of the distribution grid’s expansion • procurement and operation of the measurement data acquisition and transmission infrastructure and management of the data

Special Issue – Smart Grid

Rafał Magulski, Institute of Power Engineering, Gdańsk Division

• capture, storage, processing, and sharing of electricity consumption metering data • sharing of data about the planned and actual electricity consumption for agreed billing periods. In view of the duties and responsibilities of distribution grid operator networks, the scale of Smart Grid solution deployment depends largely on assessment of the costs to expected benefits ratio, as well as assessment of the investment risks of such projects. However, no positive assessment amounts to a deployment decision, as this will be determined also by the availability of funding, and by the feasibility of transfer of the capital costs to tariffs calculation. 2. Terms and conditions of the power system operations are specified in a Regulation of the Minister of Economy. The Regulation is the key executive act which regulates the mutual relations of power sector entities and energy consumers. The Regulation sets the terms and conditions of providing services of electricity transmission and distribution, grid operations management, grid operation / maintenance and use of the power system, as well as electricity quality parameters and customer service standards. The Regulation establishes the classification and definitions of electricity supply interruptions according to their causes (planned and unplanned interruptions), and their duration. For entities in connection groups IV and V the Regulation sets the allowable durations of one-time planned and unplanned interruptions, and the maximum aggregate durations of long and very long interruptions during a year. In a justified case, the recipient may apply for allowances for non-compliance with quality parameters and service quality standards. Distribution system operators are required to annually disclose to the public the details of electricity supply interruption durations in the previous calendar year: • average system duration of long and very long interruption (SAIDI) • average system frequency of long and very long durations (SAIFI) • average frequency of short interruptions (MAIFI). None of the currently applicable legal regulations either defines the maximum allowable indices, or provides for a penalty for their excess, and the indices’ determination and public disclosure alone do not provide sufficient incentives to take measures to improve the continuity and security of supply. 3. Rules of electricity tariff development and calculation are specifically defined in the Regulation of the Minister of Economy. Energy distribution in Poland is a regulated activity, subject to review in the process of tariff fees and rates approval. Pursuant to provisions of the Act and the Regulation, distribution companies shall set their tariffs in a manner that ensures the recovery of legitimate costs of their business, and the elimination of cross subsidies. At the same time, consumer interests must be protected against unjustified price and rate increases. The basis

Special Issue – Smart Grid

for cost legitimacy assessment are comparable costs incurred by the company in the previous year, and comparable costs of other distribution companies that operate in similar conditions. Therefore, the revenues from tariff fees represent a compromise between the level resulting from the real needs of the distribution grid extension, upgrade, and replacement, and the fee increase acceptable to the general public. 4. The scope of responsibilities of the President of ERO, in particular: • approving and controlling the use of electricity tariffs for their compliance with the rules, including analyzing and verifying the costs adopted by energy companies as legitimate to calculate tariff prices and rates • agreeing the development plans of distribution companies • organizing and conducting tenders for the implementation of projects that reduce electricity demand • controlling the customer service quality standards, and controlling, at the consumer request, compliance with electricity quality parameters • setting the inspection methods of, and taking actions aiming at, energy efficiency improvement in energy companies • releasing information to increase the efficiency of electricity use.

2.6. New Energy Law draft The now consulted draft of the Energy Law provides for significant changes in the legislation. One of these is the implementation of a so-called smart metering system. This system shall consist of smart meters along with associated ICT systems made up of a central IT application, two-way communication infrastructure, and other elements that enable remote measurements, transmission, storage, and processing of electricity metering data, and of relevant signals and commands. According to the draft’s assumptions the system should improve the country’s energy security by activating customers for more efficient management of their electricity consumption, leading to reduction of the NPS loads during periods of peak demand. According to the draft, the obligation to deploy smart meters and to connect them to the metering system shall fall on distribution system operators. They will also bear the costs of this operation which, in accordance with tariff calculation rules, will be passed on to consumers through tariff rates and fees approved by the President of ERO. The meters deployment process will be spread over time, and according to the assumptions will be implemented by the end of 2020. The meters deployment schedule and detailed terms and conditions of the smart metering system’s operations will be defined in a Regulation to the Act. Another important change will be the transfer of the responsibility for storage, processing, and sharing electricity consumption metering data, so far collected by distribution system operators, to an independent operator of metering information that shall maintain and manage

Formal and legal conditions of Smart Grid deployment

a central repository of metering information. This entity shall specify detailed rules of the smart metering operation in the form of a Metering Information Code modelled on the now applicable Transmission Grid Code. The Code shall be subject to the approval of the President of ERO. The position of President of ERO on the necessary requirements for the deployed smart metering and billing systems ERO has published a draft of “The position of President of ERO on the necessary requirements for the smart metering and billing systems deployed by RES, with consideration of the objective function and proposed support mechanisms in the postulated market model”2,

which sets out requirements for the smart metering systems for electricity consumers that are deployed by RES. Compliance with the conditions specified therein is the basis for grid operators’ applications for capex refinancing. The document contains proposals for the minimum required functionality of the system, and the relationships between stakeholders with regard to exchange of metering data, financial liabilities, and cash flows. The document is at the stage of consultation with all interested parties.

1. revision of 31.05.2011. 2. Journal of Laws No. 94, Item 551.

References 1. Directive 2005/89/EC of the European Parliament and the Council of 18 January 2006 concerning measures to safeguard security of electricity supply and infrastructure investment, OJ. Journal EU L 33/22, 2006. 2. Directive 2006/32/EC of the European Parliament and the Council of 5 April 2006 on energy end-use efficiency and energy services and repealing Council Directive 93/76/EEC, OJ. Journal EU L 114/64, 2006. 3. Directive of the European Parliament and the Council 2009/72/EC of 13 July 2009 concerning common rules for the internal market in electricity and repealing Directive 2003/54/EC, OJ. Journal EU L 211/55, 2009. 4. Directive of European Parliament and the Council 2009/28/EC of 23 April 2009 on the promotion of energy from renewable sources, amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC, OJ. Journal EU L 140/16, 2009. 5. Ministry of Economy, The Polish Energy Policy until 2030, 10 November 2009, Warsaw. 6. Ministry of Environment, Ministry of Economy, Strategy “Strategy for Energy Security and Environment. Perspective 20220” draft of 16 September 2011, Warsaw. 7. Ministry of Regional Development, National Spatial Planning Concept 2030, 25 January 2011, Warsaw. 8. The Energy Efficiency Act of 15 April 2011, Journal of Laws No. 94, Item 551. 9. The Act of 10 April 1997, The Energy Law, text unified at ERO Legal Office as of 1 January 2012. 10. The Act of The Energy Law, draft of 20 December 2011. 11. The position of President of ERO on the necessary requirements for the smart metering and billing systems deployed by RES, with consideration of the objective function and proposed support mechanisms in the postulated market model, 31 May 2011, Warsaw.

Special Issue – Smart Grid

Market aspects of smart power grids development

authors | biographies

Aleksander Babś

Maciej Makowski

Graduate of the Faculty of Electronics, Telecommunications and Information Technology at the Gdańsk University of Technology (1999) and Economics Department at Gdańsk University (2000). He has been involved in the computer industry for sixteen years. He has managed numerous implementations of high availability information systems using a specialised ICT infrastructure.

Involved with the power sector since 2008, first as a member of a project team at the ENERGA Research and Development Centre and currently working as a Product Manager at ENERGAOBROT SA responsible for the development of the Demand Response Management product portfolio and overseeing the Smart Metering and Smart Grid Projects.

Gdańsk | Poland

Special Issue – Smart Grid

Gdańsk | Poland

Aleksander Babś | Maciej Makowski

Market aspects of smart power grids development

INTRODUCTION Development of Smart Power Grids that combine power systems and smart metering AMI (Advanced Metering Infrastructure) infrastructure with state of the art ICT (Information and Communication Technology), is a development opportunity for the entire energy market, and for materialisation of the prosumer concept in particular. A prosumer is a special type of consumer, which by generating energy in microsources, effectively managing its energy consumption, or actively participating in “Demand Response”, becomes an energy market player, where through aggregation services it may even become a co-provider of services of an ancillary nature.

SMART POWER GRIDS: SYNERGY OF POWER INFRASTRUCTURE AND STATE OF THE ART ICT TECHNOLOGY The conventional operating model of companies in the power sector, and especially of distribution grid operators, is based on a simple paradigm: energy supplier (distribution system operator and seller) – energy consumer, shall be subject to significant transformation in the nearest future. One of the main change drivers is the development of IT and information transfer technologies – jointly referred to as ICT (information – communication technology), and its application in the energy sector. Already now the operation of basic power system component without ICT participation is hardly imaginable. Not to mention the importance of ICT for the further evolution towards smart power grids and the fulfilment of EU Member States’ obligations to reduce CO2, emission, the references to which are found in numerous documents, such as the report of the European Commis-

sion’s Ad Hoc Advisory Group “ICT for Energy Efficiency”, published on 24 October 2008. A model example of the ICT implementation in power engineering is development and implementation of smart metering systems, the proper operation of which requires adequate quality measuring instruments in the form of AMI (Advanced Metering Infrastructure) meters, a reliable transmission medium (very often such medium is a power grid), as well as efficient and reliable software.

POTENTIAL BASED ON INTERACTION AND SHARED STANDARDS Provision of new services to end consumers will require cooperation between DSOs and electricity sellers to a much greater extent than has been the case so far. An example of such co-operation may be transfer of electricity consumption readings from AMI systems implemented in the DSO structures to electricity sellers, or companies providing energy outsourcing services, in order to enable consumers’ use of advanced management services, and not, , as has been the case so far, for billing purposes only. Enabling consumers’ use of this type of services is one of many B2B class business processes requiring direct and relevant quality and security standards compliant communication between IT systems of concerned market players. Smart Grid development will also enable provision of ancillary services to the TSO by “active consumers” with sufficient potential of electricity consumption reduction, or even by special entities dedicated to these tasks, such as, for example, aggregators, but in specific cases also by consumers themselves. Also in this area standardi-

Abstract Smart Grids herald a revolution in the power sector. The centralized and passive power grid model known for over a century is before our very eyes assuming a completely brand new shape: of an active and dynamic network with an increasingly relevant role of consumers – prosumers, who are offered brand new products and services. Such an active development is possible due to a number of factors, such as: 1. Synergy of ICT with power engineering – these disciplines are becoming an indispensable element of the modern power grid’s operation, 2. The European Union’s regulations in the area of reduction of CO2 emission and improved energy efficiency, as well as identification of Smart Grids as one of the optimum tools, 3. Growth, thanks to continuously increasing expenditures, public awareness of the purchase and rational use of energy.

However, the Smart Grid development and ICT implementation in the power sector also carry a risk in the matter of setting up system and process links between the systems of concerned energy market players, which should be mitigated by development of technical standards, methods and principles of good cooperation between the concerned parties. Mitigation of the risk, and as a consequence, effective Smart Grids development will provide conditions for dynamic development of new roles and mechanisms on the energy market. Offering modern products and services to consumers and prosumers, and effective implementation on a national scale of demand management mechanisms will be a source of multidimensional benefits of a functional and financial nature, and will also have a positive impact on the National Lower Grid’s security.

Special Issue – Smart Grid

Aleksander Babś, ENERGA-OBRÓT SA | Maciej Makowski, ENERGA-OBRÓT SA

sation will be required with regard to interaction of the existing and developed ICT systems to enable effective actions aiming at assurance of the National Power Grid’s stability and sharing with end consumers the potential resulting from implementation of AMI and Smart Grids. The growing number of active consumers, i.e. such customers, who knowingly want to and can shape their electricity consumption profiles, and increasingly – as prosumers – can generate electricity from microsources, requires implementation of new system solutions that provide a power grid with the “smartness” necessary to ensure the power grid stability, proper power supply quality, as well as safety for the DSO’s technical services personnel. The necessary solutions involved are advanced ICT systems made up of the hardware, teletransmission, and software layers. The advent of the new and smart solutions, will enable the extension of the existing, centrally dispatched (in regard to generation sources) power grid operating model by the aforementioned active consumers and prosumers as market players of growing potential and relevance. One of the major problems in the development of IT system software is the proper definition of interfaces, i.e. the piece of software which is responsible for data exchange with other systems. The service interfaces of Smart Grid applications will have the key role in building a well functioning market of services for all participants of the electricity market. Given the national market model: a single TSO – individual DSOs – multiple sellers, and the required possibility of interaction between all the aforementioned groups, standardisation is advisable in the area of B2B and B2C processes. Consistent actions of the market participants on the basis of the implemented standards allow for their efficient co-operation, now however – in the face of the Smart Grid development – this operating formula will be extended both horizontally and vertically. New services for electricity consumers will be practically entirely based on consistent and business-oriented cooperation of the market players: the TSO, DSOs, and electricity sellers. The standardisation of key relevance for this cooperation development will relate first and foremost to agreeing upon a common language to be used in communication between the market participants. Besides the language, it will be also necessary to set appropriate communication channels. Despite the rapid development of Smart Grids and definition of standards, which advances in parallel to implementation of solutions based on these standards, it’s possible to employ well established information exchange and information definition standards.

detailed description of such an approach is provided by a series of standards such as: IEC 61970 (Energy Management System Application Program Interface, EMSAPI), IEC 62325 (including definitions, i.e.: Deregulated Energy Market Communication and Framework for Energy Market Communication), or typically operator activity oriented: IEC61968. Conversation channels, i.e. transfer and exchange of standardised CIM messages can be carried out withinSOA (Software Oriented Architecture), which is utilised by major business applications in large companies and corporations. On the basis of SOA, large centralised ecosystems may be created, whereby information forwarded by market players is centrally collected and processed (like in the WIRE system – Energy Market Information Exchange in Poland), as well as decentralised structures based on standardised peer-to-peer communication (like for example the global cooperation of mobile telephony operators using the TAP protocol that enables unrestricted exchange of roaming calls billing details). It is advisable that the electricity market players on the supply and distribution side start implementing the mechanisms listed above as soon as possible. Their implementation will enable offering modern products to consumers. From the consumer point of view these services will provide new opportunities, first and foremost with regard to rationalisation of electricity consumption and improved efficiency of its use.

The information definition – as a language itself – must be based on clearly specified and comprehensible rules for the communication parties, and it also must have a defined syntax. An example of such common language is the concept of CIM (Common Information Model), which enables modelling in a standard way most of the data (objects) present in a power company, and determining a standard form of their recording. A

NEW ENERGY MARKET PLAYERS

Special Issue – Smart Grid

TSO

Consumer

Aggregator

Prosumer

Electricity seller

Information flow

DSO

Energy flow

Fig. 1. Flow of information and energy in Smart Grid between market players

Availability of the infrastructure enabling the launch of new products to the electricity market will stimulate the emergence of new specialised entities that will be able to offer modern services to customers, as well as perform brand new roles in the energy market. High growth rate is particularly evident in the areas of energy efficiency and energy demand aggregation.

Market aspects of smart power grids development

ESCO companies ESCO acronym (Energy Service Companies) is commonly used in Western countries to denominate a power services provider that offers comprehensive expert services in the power sector, and warrants potential customers’ energy savings and reduction of energy bills. ESCO companies provide comprehensive energy management services under executive contracts, and grant energy saving guarantees. ESCO companies, on the basis of precise and available in real (or near real) time electricity consumption measurement data will be able to offer on a large scale to their customers, energy consumers, professionals services related to energy consumption and demand reduction. The fee for the services is typically generated by the customer’s reduced energy bills. The scope of the services may include not only energy usage efficiency improving projects, but also equipment maintenance and repair, cogeneration of electricity and heat, new technologies, and alternative electricity generation, if only the fee for these services originates from the accomplished savings1. Aggregators – demand management In Smart Grid solutions two-way electricity flow in grids is a paradigm. This means that electricity can flow not only from central sources to end consumers, but can also be generated by consumers and fed by them into power grids. The coexistence of the above trends is proven by the increased consumer activity on the energy market. An active consumer’s actions may include informed consumption reduction, altering usage patterns in time and energy generation using microgeneration sources. The emergence of active consumers as well as the two-way electricity flow account for a new area, within which many technological solutions have been recently conceived. From the Smart Grid viewpoint the demand response and distributed generation management concept consists of two basic elements: • controlled demand reduction (controllable loads aggregation) • energy supply aggregation – in the meaning of the Virtual Power Plant concept, whereby small sources play an important role – and support for their deployment is a commercially significant element of the demand response and distributed generation management.

SMART CONSUMER GRIDS – BENEFITS, MODERN SERVICES In order to accelerate the Smart Grid deployment processes and acceptance, activities within the field of consumer value creation and appropriate communication based on potential benefits need to be intensified. On the electricity distribution side the Smart Grid deployment’s benefits for consumers will primarily consist in rarer occurrences and shorter durations of electricity supply interruptions. Owing to better observability of medium voltage grids, faults of which to a large extent affect SAIDI (System Average Interruption Duration In-

dex) and SAIFI (System Average Interruption Frequency Index) indices, faulty grid sections can be isolated in order to restore supplies to healthy grid sections. Another benefit from the Smart Grid deployment is the option to implement a system of public information on the electricity supply status and the other events in the power grid of relevance to the safety of local communities [3]. Such a system, using a dedicated web service, would present details of the current condition of a given grid area retrieved from the Smart Grid system. This way local residents, businesses, and authorities would acquire access to details of the current electricity supply status and problems, if there are any, related to its transient interruption. Examples of product deployments, the complete success of which require Smart Power Grids, and which will bring about numerous benefits, include the following: • Sharing with electricity consumers complete energy consumption information in the form of reports and charts available through the Internet and with the use of portable devices, and enabling better understanding and modification of energy consumption patterns. Departure will be possible from the conventional model of electricity billing based on forecasts in various intervals 6-month even, as instead the settlement is proposed as per the actual meter reading at any interval at the consumer’s convenience and discretion • Introducing the option of participation in demand management programmes and making the available to consumers – prosumers • Development of the Home Area Network as the management centre for the house, energy efficiency, and – ultimately – a platform of offering value added services • Ease of microgeneration sources deployment and management, renewable ones in particular, and widespread use of electric vehicles not only for transport, but also as elements of the demand management mechanisms or electricity storage (Vehicle-2-Grid concept). In the context of the Polish power sector’s technical and operational conditions the aspect of demand management and potential programmes that may be offered to consumers seems to be particularly worthwhile. The implementation of such programmes may be beneficial not only for them, but also for sellers, the TSO, and DSOs. The demand management is typically divided into the following two basic areas: Incentive programmes – enabling the reduction of the maximum peak loads, when the ratio of energy price paid by consumer to purchase costs is high resulting from events such as, for instance, energy supply shortage or increased overall demand. These may include: • programmes whereby the energy seller initiates activities leading to energy consumption reduction • as well as programmes that require the consumer’s decision to reduce the consumption (or to shift it in time) based on appropriate price incentives.

Special Issue – Smart Grid

Aleksander Babś, ENERGA-OBRÓT SA | Maciej Makowski, ENERGA-OBRÓT SA

Pricing programmes – which require the consumer’s decision to reduce the consumption (or to shift it in time) in specific times of the day, based on pricing incentives offered by energy supplier. The most popular groups of pricing programmes include: • Time-of-Use pricing (TOU pricing) – electricity prices change in the daily, weekly, and seasonal (summer/ winter) cycle. Price rates are set for longer periods. TOU tariffs provide consumers with incentives to reduce the energy consumption at load peaks, and to use electricity when its prices are low (in a load valley) • Real time tariffs RTP (Real Time Pricing) – provides for electricity price variability throughout a day. Electricity price rates vary similarly to wholesale market prices, while consumers are informed of projected energy prices in advance of one hour up to one day • Tariffs with peak price option CPP (Critical Peak Pricing) – a specific variety of ToU tariff, whereby rates are strictly tied up with the power system’s current operating conditions. Some CPP tariff varieties introduce one or two additional very high rates for the system’s peak loads, i.e. the periods when the wholesale market prices are the highest. Consumers are informed at short notice that the rates will apply, and their amount and validity period are set by the energy supplier. The programmes presented above are only examples of demand management tools, the availability of which will be possible along with the Smart Grids deployment, and which facilitate consumption reduction in peak periods or shift to a non-peak period. As a result, the smoothing of the daily energy demand curve can be observed, which is good for the national power grid, while at the same time providing consumers with tools for better understanding and rationalization of expenditure on electricity.

SMART GRIDS FUTURE IN THE CONTEXT OF OFFERED SERVICES AND CONSUMER ROLE The power system of the future will be based on the following two key pillars: Smart Grids and specialised energy management systems. Smart Grids will provide an accessible and safe infrastructural platform and will be managed by DSOs, and in some selected areas by the TSO as well. The energy management systems will belong to the sphere of competence of electricity sellers or specialised entities such as, for instance, aggregators. In a longer run it may turn out that the strict interdependence of the both system will evolutionary lead to the emergence of energy agents, i.e. autonomous entities continuously communicating with each other and implementing their own strategies in the context of the whole power system. The agent, as meant by the foregoing assumption, may be practically any receiver, device, or object connected to a power grid and provided with an appropriate controller with its own efficiency and optimisation algorithm with the option of unrestricted communication with other agents. In the system such agents will represent consumers, prosumers, energy sellers, large generators and grid operators at all levels. The agents’ interrelations will be dynamic, and they will be automatically pursuing the maximisation of their own objective functions based on exchanged signals, for example: temporary and maximum allowable power grid operation parameters, prices of electricity from available sources, current and planned capacities of these sources, customers’ tendency to consume a specific volume of energy at a specific price. In the light of the currently conducted research and pioneering efforts undertaken in the area of providing the theoretical basis for operation of the energy agents model, Smart Grids may be just a stopover in creating the power infrastructure of the future, which will ultimately shape consumers’ behaviours and demand for the whole new set of energy market related services.

1. “Firma usług energetycznych – ESCO” – Marek Butkowski, PSE – Wschód sp. z o.o.

References 1. The Smart Grid – Lunch and Learn, GE Power 2011, http://www.usea.org/USEA_Events/Smart-Grid-Briefings/Ses– sion_2-The_Smart_Grid-The_Consumer_View.pdf. 2. Smart Energy Management: Decentralised Collective Demand – Response Management in Smart Grids, http:// www.swinburne.edu.au/ict/success/research-projects-and-grants/smart-energy/. 3. Krohns H. et al., Demonstration of Communication Application for Major Disturbances in the Supply of Electric Power, Conference CIGRE 2011 – The electric power system of the future, Bologna 2011. 4. Studium wdrożenia inteligentnego pomiaru energii elektrycznej w Polsce [A study of the smart electricity metering deployment in Poland], Polish Society for the Transmission and Distribution of Electricity in cooperation with Institute of Power Engineering, Gdańsk Division and Ernst&Young Business Advisory sp. z o.o. 5. “ICT for Energy Efficiency”, Report of the European Commission’s Ad Hoc Advisory Group, Brussels 2008. 6. “Firma usług energetycznych – ESCo” [An Esco company], Marek Butkowski, PSE – Wschód sp. z o.o.

Special Issue – Smart Grid

A vision of Smart Grid deployment at ENERGA-OPERATOR SA

authors | biographies

Sławomir Noske

Adam Babś

Chief R&D Engineer at ENERGA-OPERATOR SA. Has been employed in the power company since 1991. Graduate of Poznań University of Technology, Faculty of Electrical Engineering. He completed postgraduate studies in the legal and management field at the Gdańsk University of Technology and MBA management studies, organized by the Gdańsk Foundation for Management Development. In 2006 he was admitted into the Ph.D. program “Diagnosis of medium voltage cable lines with the use of partial discharge test using the self-damping voltage wave method”.

Department manager at Institute of Power Engineering. Scope of interest covers Smart Grid and smart metering system, dynamic line rating, data exchange standardization. Participates in power system automation projects in many places in the world. He has authored or co-authored dozens of technical papers and research studies.

Gdańsk | Poland

Krzysztof Madajewski Gdańsk | Poland

Since 1990 director of the Institute of Power Engineering, Gdańsk Division. A specialist in the field of control and regulation of power systems. Participate in activities of the EERA (European Energy Research Alliance) in groups of Smart Grid and Wind. Represents Poland in EEGI (European Electric Grid Initiative), dealing with network issues, particularly the Smart Grid at the EU level.

Special Issue – Smart Grid

Gdańsk | Poland

Sławomir Noske | Adam Babś | Krzysztof Madajewski

A vision of Smart Grid deployment at ENERGA-OPERATOR SA INTRODUCTION According to research – including but not limited to report “Impact of Smart Grid Technologies on Peak Load to 2050 “, compiled by the International Energy Agency (Fig. 1) – it is indicated that in the European Union, in the perspective of 2050, the market share of renewable energy sources will have a critical impact on grid development.

Growth in electricity demand Increase in peak load Deployment of renewable energy sources Use of Evs PHEVs for peak management 2010

2020

2030

2040

Low impact

high impact

medium impact

verty high impact

2050

Fig. 1. Impact of key elements on Smart Grid development in the European OECD countries

The developmen of the power sector in the European Union, including Poland, in the coming years will depend on sustainable development, and will be based on common use of renewable energy sources and increased energy consumption efficiency. Changes in the generation structure, including the widespread use of distributed energy sources, will result in: • growing importance of large grids for connection of load centres and large centralised renewable generations • emergence of small local grid clusters that provide ancillary services including decentralized local generation, energy storage, and active consumers • two-way flow of information and electricity • need for dynamic management of generation and load alike. A future power grid will have to encourage and integrate in a smart way actions and behaviour of generators, consumers, and other energy market players, so as

to provide reliable, economically viable and sustainable electricity supplies of electricity. This will entail the need to deploy Smart Grid solutions on a large scale, thus procuring a power system which will be: • optimal in terms of infrastructure use • proactive, and not only responding to occurrences of critical situations • distributed regardless of geographical or organizational constraints • integrated, combining a variety of systems • self-healing and adaptive. Distribution systems operators (DSOs) will have to cope with resulting challenges and expectations, developing their own strategies, taking into account differences between each DSO in terms of their structure and management, as well as differentiated local circumstances. ENERGA-OPERATOR SA, as part of preparing a road map the Smart Grid development, has completed the first stage of the work, specifying a vision of deploying state-of-the-art solutions in its grid and its extension up to the Smart Grid level. Work on this document resulted directly from the strategy of ENERGA-OPERATOR SA. The strategy envisions the company’s development through focusing on the following three pillars: • innovations – search for new, original solutions both in the area of development of its assets, as well as refining its organization • investment – capital expenditure projects aiming at the upgrade and development of its distribution assets • initiative – efforts towards the widest possible involvement of the company’s staff in its development. Analysis of the current condition and determining the key challenges that ENERGA-OPERATOR SA faces allow determining a vision of Smart Grid development in the area of the company’s business. The sources of problems already include, or will include in the near future, the following: • social and environmental constraints to infrastructure deployment • distribution grid’s inadequacy for future functions, • MV and LV grids’ insufficient observability

Abstract ENERGA-OPERATOR SA as a power distribution system operator is working on preparing its network for current and future challenges facing the energy sector. The strategy will be based on a smart grid development plan to be carried out by

ENERGA-OPERATOR SA. The article describes key elements of the smart grid implementation vision which is the first stage of the work on the smart grid development roadmap.

Special Issue – Smart Grid

Sławomir Noske, ENERGA-OPERATOR SA | Adam Babś, Institute of Power Engineering, Gdańsk Division |Krzysztof Madajewski, Institute of Power Engineering, Gdańsk Division

• local accumulation of dispersed generation and the associated change in the power transmission direction (from DSO to TSO) • projected generation capacity deficit, probable after 2016.

STAKEHOLDER EXPECTATIONS FROM DSO Another element which was considered in drawing up the Smart Grid development vision, were stakeholders’ expectations from the distribution grid operator. The analysis and expert work have allowed defining the stakeholders’ key expectations from OSD, which are presented in the table below.

CHALLENGES FOR ENERGA-OPERATOR SA ENERGA-OPERATOR SA and other distribution grid operators alike are now facing many challenges. Each of these entails the need to undertake specific actions: • to improve the reliability and security of electricity • supply and to ensure electricity’s high-quality

Subject

Expectations

Consumers

• higher reliability - fewer power supply interruptions • shorter after fault recovery time • better information on outages and after fault recovery times • improved quality of customer service by the DSO and seller • improved quality of supplied electricity • lower costs of the distribution and transmission service • higher ROI • increased operational efficiency • optimisation of capital expenditures • improved quality of services provided to consumers • increased operational efficiency • compliance with recommendations, transparency and predictability of operations • coordination of grid development plans considering the dynamic development of distributed generation • implementation of a new ancillary service provision model considering the new generation distribution in the system and the new role of active consumers • implementation of a new system dispatch model, and of new standards of TSO power dispatch with DSOs • minimizing the adverse system effects resulting from variability in the direction of power flow between the DSO and TSO grids

DSO owner

Regulator (ERO)

Transmission system operator (PSE Operator)

Investors in distributed generation development, incl. RES

Society, public opinion

Electricity sellers

Technical solution vendors

• to optimize the use of existing infrastructure and organizational resources • to improve the distribution grid’s energy efficiency, • to provide opportunities for an increased active role of consumers in the management of electricity consumption and generation • to integrate distributed sources and system • balancing in the conditions of a growing share of • distributed and dispersed generation • preparation of technical and organizational solutions for DSO involvement in system balancing on the distribution grid level • improved accuracy of distributed generation output forecasts • system’s preparedness for massive implementation of electric vehicles a significant part of these challenges can be met by implementing new innovative solutions related to Smart Grid development.

• efficient and effective procedures of switching decisions • adjustment of the grids and dispatch systems infrastructure to investors’ conclusions and expectations • elimination of the attributable to DSO causes for constraints to outputting power from distributed generation • grid’s resiliency to damage and weather conditions • reduction of the burden on surrounding environment • reduction of CO2 emissions • efficient and credible notification of the effects of implemented changes • better information about supply interruptions, transmission capabilities, and grid operations • option to ensure two-way communication with customers using the DSO infrastructure • option to obtain detailed data on electricity consumption, including consumption profiles • clear signals from DSOs as to expected capex project directions • transparent specifications of services and equipment to be procured • transparent schedule of expected procurement

Special Issue – Smart Grid

A vision of Smart Grid deployment at ENERGA-OPERATOR SA

SMART GRID COMPONENTS From the perspective of DSO, and therefore also of ENERGA-OPERATOR SA, a Smart Grid consists of distribution and ICT infrastructure elements so far in use, but also new solutions that appear along with technological progress. These include: • power lines and substations • measuring systems and control devices • telecommunication infrastructure and data collection and exchange platforms • grid management and business process support systems.

Power lines and substations Conventional grid infrastructure primarily included 110 kV (HV) lines, medium voltage (MV) lines, and low voltage (LV) lines, both cable and overhead, as well as switching substations that cooperate with the national 400 kV and 220 kV transmission grid and account for the main supply points for the 110 kV grid, and also substations in the MV grid where electricity is transformed to low voltage for individual consumers’ supply. This infrastructure’s upgrade and extension will take into account Smart Grid deployment related requirements. Therefore, it will not be a simple multiplication of existing models, but implementation of advanced technical solutions. These will enable supervision of equipment, self-diagnostics, monitoring, and adjustment to heavy weather conditions (resilience to weather changes). Technical standards then developed should accept and promote deployment only of equipment that meets the new technical requirements, so in the perspective of a few years the grid infrastructure will support Smart Grid solutions. Measuring systems and control devices These elements are designed to measure the grid status, and implement autonomous automatic functions related to the assurance of continuity and reliability of electricity supply to consumers. In general, this class of systems and devices is referred to as a substation’s “secondary circuits”, and their most important part are the automatic protection systems. These include sensors and convertors of electrical (voltage, current, power) and non-electrical (temperature, pressure) parameters, auxiliary relays, and control devices. Smart Grid of the future will be provided with many more such systems than now, especially in medium and low voltage grids. The most important change will be widespread installation of smart electricity meters at each consumer by 2020, capable of measuring many electrical values. Telecommunication infrastructure and data collection and exchange platforms The telecommunication infrastructure will be a key Smart Grid element. It will ensure the ability to transfer significant data volumes from consumers and devices to decision-making centres as well as in the opposite direction. In this way it will deliver information enabling

grid management and control, as well as implementation of functionality that requires information exchange with end consumers, i.e. demand management and load control. Telecommunications infrastructure development will be one of the most important Smart Grid deploymentrelated undertakings, and the functions implemented will become the basis of the new grid’s operations. Data acquisition and sharing with other systems and entities (power companies, consumers) will be an essential requirement for Smart Grid. This refers to data such as: • data common for the entire company, stored at a central database (data warehouse) • application oriented data (system analysis, engineering calculations) • local data of specific acquisition and sharing rate requirements, mostly used for advanced technical realtime applications, such as system automation and control. Essential differences compared to the currently collected data will refer to the following issues: • enormous volumes of data that will have to be managed • the need to adopt a single and consistent data model suitable for various needs, and for exchange with other entities in particular • the need to ensure data security and confidentiality, including resistance to catastrophes of large magnitudes • the need to ensure high data quality and synchronisation.

Grid management and business process support systems Grid management and business process support systems are currently operated as stand-alone and loosely interoperable systems. Smart Grid deployment will entail the following changes: • integration of applications within a consistent IT environment based on new ICT technologies • development of new applications dedicated to Smart Grid analysis and business process support-related needs • assurance of IT security to an extent adequate to future needs. • The main change areas will refer to such groups of applications, as: • SCADA systems and grid management systems • DMS systems, including those featuring the grid fault location and isolation option and remote grid reconfiguration • GIS geographic information systems, and grid assets management system • electricity metering systems for individual and industrial consumers • advance systems of weather, statistical, and measurement data-based forecast that enable resource use optimisation

Special Issue – Smart Grid

Sławomir Noske, ENERGA-OPERATOR SA | Adam Babś, Institute of Power Engineering, Gdańsk Division |Krzysztof Madajewski, Institute of Power Engineering, Gdańsk Division

• engineering support and assets (infrastructure) management systems.

SMART GRID DEVELOPMENT PRIORITIES Given the current issues arising from the distribution grid condition, challenges expected in the coming years, as well as from the legal conditions, ENERGA-OPERATOR SA’s actions related to Smart Grid development should focus in the near future on the following five areas indentified in the Smart Grid deployment vision: 1. Active customer – the provision of conditions for stimulation of consumers’ activity in the area of electricity consumption and generation 1.1. Smart metering systems 1.2. Demand management infrastructure 1.3. Grid infrastructure and procedures adjustment to distributed generation 1.4. Infrastructure and management structure for electric vehicles 2. Quality of supply – the improvement in reliability of customer supply and quality of supplied electricity 2.1. Distribution grid’s widespread automation on the MV level 2.2. Smart solutions for 110 kV/MV substations 2.3. Increase in grid observability 3. Smart Grid control – the advanced grid management and control in the conditions of dynamic development of distributed generation 3.1. New model of operations control and dispatch 3.2. Load management systems 3.3. Smart management of distributed generation 3.4. Innovative systems of grid planning and management support 4. Smart DSO – the optimal use and development of DSO asset and organization resources 4.1. Distribution grid development 4.2. Grid assets management systems development 4.3. Development of grid operation services management tools 5. ICT technology – Development of technology for Smart Grid control 5.1. ICT network for Smart Grid 5.2. Service oriented information architecture 5.3. Standardisation of ICT solutions 5.4. IT security

EXPECTED BENEFITS Implementation of the Smart Grid concept will increase the power system’s flexibility, and will allow benefits for all participants in the value chain, from generators, grid operators, service providers, up to end users and society. Benefits from the Smart Grid concept implementation assigned to individual stakeholders are presented in the table below.

MAIN BARRIERS TO IMPLEMENTATION Main barriers identified by ENERGA-OPERATOR SA, which may impede the smart gird concept implementation include the following:

Special Issue – Smart Grid

• social resistance to the deployment of new technologies • incompatibility and instability of regulatory arrangements • rapid obsolescence of technologies • uncertainty with regard to standards • large-scale investment and the associated risks arising from unsuccessful investment • need to prepare staff to implement Smart Grid solutions. Efficient and effective implementation of new smart solutions and development of power grids tailored to future needs require many changes in the existing legislative, regulatory, market, and technical solutions. Their main aim should be to create better regulatory conditions for DSO investment of considerable funds in Smart Grid development. The scope of the necessary regulatory amendments is broad; the most relevant postulated changes include the following: • actions at the EU and national level that encourage implementation of long-term solutions to ensure stable and appropriate rate of return from investment • substitution of the existing cost only based regulatory model with one which considers electricity supply quality and provides DSOs with an incentive for innovative actions • assurance in tariff of return of the investment in Smart Grid solutions’ development • provision of a redistribution mechanism of the social benefits from Smart Grid deployment that favours entities that invest in such solutions and are involved in demand response management related projects • definition of the division of roles and responsibilities between the transmission operator and distribution system operators, especially with regard to grid operations management and supervision in the centrally dispatched network • changes in the energy market model that encourage consumers towards active and flexible behaviour with regard to energy consumption • provision of solutions that would enable adjustment of energy supplier offerings to individual consumption profiles and consumer preferences • regulatory support to development of the ancillary serviced market, with regard to both demand response management and distributed sources management. ENERGA-OPERATOR SA intends to actively participate in efforts to support changes in all the abovementioned areas.

SUMMARY The “Vision of Smart Grid deployment at ENERGAOPERATOR SA”, some selected excerpts of which are presented here, is the first step towards developing a detailed road map of the Smart Grid development. Subsequent planned actions are meant to lead to developing the road-map by the end of 2012. It is planned to leverage in these works on the expertise and experience of EN-

A vision of Smart Grid deployment at ENERGA-OPERATOR SA

Stakeholder

Expected benefit and its fulfilment

Electricity consumers

• reduced number of consumers not supplied during fault due to extended remote grid monitoring, control, and defect fault location • reduced fault frequency due to grid improvements owing to better information on its components’ condition • significant reduction of grid fault location and liquidation (repair) • reduced number of outages due to better quality of dispatcher’s decision-making based on better grid obeservability • improved quality of supplied electricity • availability of efficient sharing of fault location and type of data with consumers

Electricity sellers and other market players

• availability of new product and service offerings, including, but not limited to, demand response management programmes • improved customer service quality in terms of access to precise data on electricity supply and consumption

Power system

• optimal grid development taking into account the dynamic development of distributed generation • option to implement a new, more optimal model of ancillary service provision considering the new generation distribution in the system, and the new role of active consumers • option to implement a new more optimal model of system operations dispatch, and of power dispatch interaction standards • minimizing the adverse system effects resulting from variability in the direction of power flow between the DSO and TSO grids

Investors in distributed generation sources

• adjustment of the grids and dispatch systems infrastructure to investors’ conclusions and expectations • reduction of the causes of constraints to outputting power from distributed generation attributable to DSO

ERGA-OPERATOR SA staff, as well as to utilise the support of external companies and R&D organizations, and

also those with international experience in implementing similar projects.

Special Issue – Smart Grid

Smart Grids – selected objectives and directions of distribution system operator actions

authors | biographies

Rafał Czyżewski

Adam Babś

Chairman of the Board of ENERGA-OPERATOR SA. A member of the company Board since December 2008. Actively participates in national and international projects of development of regulatory and engineering solutions for Smart Grids. A representative of the Polish power sector in the European Commission’s working groups within the framework of the European Industrial Initiatives (EII). A Board Member of the Polish Society for the Transmission and Distribution of Electricity. Previously, he supported enterprises in the process of their restructuring.

Gdańsk | Poland

Krzysztof Madajewski Gdańsk | Poland

Special Issue Edition – Smart – Smart Grid Grids

Gdańsk | Poland

Rafał Czyżewski | Adam Babś |Krzysztof Madajewski

Smart Grids – selected objectives and directions of distribution system operator actions 1. INTRODUCTION Smart Grids have for a long time taken a prominent place in programs and publications related to grid development. This paper focuses on discussing selected objectives to be achieved and directions of action to be taken in the next ten years by the distribution system operator (DSO). A more extensive discussion of these issues with regard to the national DSO, and to ENERGA-OPERATOR SA in particular, can be found in [5]. Smart Grids entail a wide application of innovative solutions. These solutions will address new and innovative applications of, in most cases already existing, technologies in electric and IT networks and in the energy market. The main current challenge is the integration of modern solutions in efficiently and effectively operable systems in the complex environment of grid operators. Smart Grids are not just a modern infrastructure, but new products and services offered for the benefit of the customer. The role of the operator will be to provide a modern, functional, and energy-efficient infrastructure that enables service providers’ and electricity generators’ competitive and unfettered operations in the conditions of a growing share of distributed generation and active role of energy consumers. In Europe EUR 5.5 billion has been invested in the last decade in approximately three hundred different Smart Grid projects. It is estimated [3] that about 15% of the expected investment in Smart Grids will be allocated to the launch of smart metering systems, and 85% to the upgrade of the rest of the system.

2. PREFERRED DIRECTIONS AND OBJECTIVES OF ACTIONS AT THE EU AND NATIONAL LEVELS Smart Grids are of interest to distribution companies of all countries, including EU Member States. At the EU, in the framework of industrial technologies SET Strategic Energy Technology Plan the EEGI European Electricity Grid Initiative group was appointed. A study [7], published in January 2012 as the subsequent result of EEGI work, presents the current achievements and

future plans, as well as the needs of Smart Grid technology development in distribution companies in EU countries. In April 2011 the European Commission in its communication to the European Parliament COM (2011) 202 – “Smart Grids: from innovation to deployment” indicated the need to: • develop and implement technical standards • ensure receiver data security • define a time framework for national regulator actions in the area of power engineering in order to provide incentives for deployment of Smart Grid solutions • guarantee an open and competitive energy market for customers • ensure consistent support for innovations in the technology and system areas. The Commission states in the communication that it intends to refer a request to the Member States for development of action plans for Smart Grids with an indication of specific targets to be achieved. In the longer term in the Commission’s Communication “A Roadmap for moving to a competitive low carbon economy in 2050” Smart Grids were considered the major factor enabling the development of a future low-carbon power system that increases efficiency on the demand side, the share of renewables and distributed generation, and enables electrification of transportation. In February 2012 the European Commission reactivated the SGTF Smart Grid Task Force that includes teams of experts in: • standardisation • data confidentiality and security • regulatory solutions for Smart Grids • infrastructure deployment. The names of the teams clearly indicate the objectives and directions of activities of interest to the European Commission.Very important for acceleration of the Smart Grids deployment in the EU is the European Commission’s position reported in Article 12 of the draft directive on energy efficiency, indicating the need for the implementation of national regulatory arrangements to encourage Smart Grids deployment.

Abstract The paper presents various aspects of the implementation of Smart Grids from the distribution system operator standpoint. It discusses legal conditions of the Smart Grids implementation and their impact on the implementation timing. It describes the current state of the distribution grid and operations management systems infrastructure, indicating the desired direction of their development. It describes the preferred

model of interrelations between grid operators and other key stakeholders, especially in the context of the expected establishment of balancing areas. It points out to the relevance of standardization and to the assurance of security of implemented Smart Grid solutions. It also specifies the barriers, which in the authors’ opinion could impede the Smart Grids deployment.

Special Issue – Smart Grid

Rafał Czyżewski, ENERGA-OPERATOR SA | Adam Babś, Instytut Energetyki Oddział Gdańsk Krzysztof Madajewski, Instytut Energetyki Oddział Gdańsk

The Commission believes that the introduction of Smart Grids to the competitive retail market should encourage consumers to change their behaviours, to be more proactive, and to adapt to the new ‘smart’ energy consumption patterns. It is a necessary condition for successful transition to an efficiency-based business model. The basis of the new model is responding to demand. It requires ongoing interaction between energy suppliers and energy management by the customer and a much wider use of electricity price differentiation depending on the time of the day and day of the week, so that the customer has a real incentive to change consumption patterns. In Poland one of the most important changes in the power sector is the introduction in the draft of the new Energy Law of the obligation to deploy a smart metering system. It is expected that the key objectives, the implementation of which will ensure the deployment of this system, include [6]: • increased energy security of the state through developing the technical capacity to flexibly manage the demand for electricity, particularly in crisis situations; • increased effectiveness of electricity consumption and its rationalisation • improved market position of energy consumers in relation to sellers. According to this draft of the new Energy Law, the obligation to install smart electricity meters and to connect them to the metering system shall rest with power distribution system operators. It is assumed that the obligation should be enforced by all DSOs by the end of 2020. A very important role in the development of Smart Grids is assigned to the Energy Regulatory Office. On June 2, 2011, a position was posted on the ERO webpage on the necessary requirements for smart metering and billing systems. Work is underway on new documents, including the determination of detailed requirements for the Home Area Network area – smart home networks, and for regional microgrid functionality.

3. PRESENT STATE OF INFRASTRUCTURE AND OPERATOR SYSTEMS Effective and efficient adjustment of the distribution network to future challenges requires the identification of problems that grid companies face now and will face in the near future. The problem sources already include, or will include in the near future, the following [5]: • social and environmental constraints to infrastructure deployment • incompatibility of the distribution network with future functional requirements –– the current grid has been developed as a passive network suited to the flow of power “top down”, whereas the future grid will be an active network, to which significant generation volumes are connected –– DSO will become more involved in balancing the system and, more generally, in the provision of system services that are currently the TSO domain

Special Issue – Smart Grid

• insufficient observability of MV and LV grids resulting from the absence of adequate metering • local accumulation of dispersed generation • aging infrastructure resulting in increased failure rate and decreased energy efficiency of DSO grids • reversed power flow – from DSO to TSO • uncertainty in grid development planning under the new generation structure. The approach to assessing the current state of the grid, IT, and DSO management and support systems infrastructures should allow qualitative and quantitative evaluation of the implemented Smart Grid solutions’ impact on improvement of some selected indicators, i.e. the final outcome. Demonstration of Smart Grids’ effectiveness and efficiency in accomplishing adopted objectives will indeed be the main premise for their widespread deployment. Benefits for customer, the environment, and the power system are of key significance here. Therefore, the proper definition, recording and presentation of the impact of new solutions implemented by the operator enables achieving benefits for: • customer, in terms of increased: –– energy supply security and reliability –– energy quality –– opportunities for active participation in load management –– satisfaction with the quality of services • the environment, in terms of: –– quantitative reduction of CO2 –– increased share of renewables in energy supply –– increased number and output of distributed generation sources • the power system, in terms of: –– decreased grid loses (increased energy efficiency) –– improved system operation security –– increased system operation management flexibility. For each of these elements it is possible and advisable to adopt uniform standards for quantitative assessment of the impact of the Smart Grid deployment on their values. This will be very important in demonstrating the results obtained from the Smart Grid deployment, especially in the tariff formulation dispute with the ERO.

4. DIRECTIONS OF DISTRIBUTION GRID OPERATOR ACTIONS The purpose of Smart Grid deployment in the ENERGAOPERATOR SA distribution network is to achieve tangible benefits. In the next few years the actions will focus on the five thematic areas more widely discussed in [5]: • facilitating stimulation of customer use and generation of energy • improving the reliability of customer supply and the quality of supplied electricity • advanced network management and control in the conditions of dynamic development of distributed generation • optimal use and development of DSO property and organisation resources

Smart Grids – selected objectives and directions of distribution system operator actions

• development of information and communication technologies for Smart Grid control.

5. DSO COOPERATION WITH OTHER STAKEHOLDERS Very important for the efficiency and effectiveness of the Smart Grid deployment process will be the adoption of an appropriate model of the interrelation action between network operator and other key stakeholders, such as: • transmission system operator • electricity generators (distributed sources incl. renewables) • aggregators (on the reception and the small generation sides alike) • trading companies • ESCOs1 – companies dealing with efficiency improving projects and services • energy storage operators and VPPs (Virtual Power Plant). Adoption of a new interrelation model already in the near time perspective could lead to changes in the power grid operations pattern and to formation of local systems, which operate as separate balancing areas. A factor accelerating the formation of such areas is the development of smart solutions and energy storage. A positive effect of such changes will be improved energy supply security and distribution and transmission grids’ operations. The formation of local balancing areas in the distribution grid will also change the tasks previously performed by distribution grid operators, involving the provision of services to active players, such as: generators, aggregators, ESCOs, active customer, etc. It may be expected that DSOs will be responsible for preparing and maintaining the infrastructure needed to provide such services. It follows from current legal arrangements that a distribution grid operator won’t be able to directly offer any new products and services to customers, and its task will be limited to the provision of technical infrastructure and fair competitive conditions and transparent operations with this respect to electricity generators and service providers. The success of the Smart Grid deployment in large part will depend on the new range of products and services provided by electricity generators and service providers. Changes in the model of interrelations with the transmission system operator will be related to factors such as: increased share of distributed generation connected to the distribution grid, mass deployment of AMI systems, new active role of consumers, possibility of participation of entities that aggregate electricity consumers and / or small producers with VPP (Virtual Power Plant) managers in the system services provision. These factors will cause the need to define a new interrelation model, including sharing the responsibility for power system operations security, and procedures and standards of interoperability in system operations management. An increased share of electricity producers in distribution grids makes the grids increasingly active. This

carries a lot of challenges in the management of this generation, as well as technical problems resulting from changes in power flows, voltage profiles and grid elements rating. At the same time the increased share of generation connected to the distribution network creates new opportunities and needs in the provision of system services by these sources. Their proper use requires a new model for the provision of such services so far centralized and managed only by the transmission system operator. Trading companies, aggregators, ESCOs, and energy storage operators are the group of entities that will be responsible for the broadly defined market success of Smart Grids. These entities will be able to offer attractive products and services for their customers, and tailored to demand system services for grid operators. An important factor will be the evolution of the tariff offering for customer. The activities performed in competitive conditions will improve the energy efficiency on the sides of customers, generators, and the grid itself. The need to enable operations of many different entities will require a unified and coherent resolution of principles of cooperation and the adoption and implementation by the network operator of recognized technical standards, including data communication standards and organizational models. These and other activities that generate costs for the operator must be properly standardized and fairly compensated within the grid operator’s regulated operations.

6. STANDARDISATION OF SOLUTIONS AND INFORMATION SECURITY Very important for the effective and efficient Smart Grid deployment will be appropriate information architecture. It is the basis of business and technology in Smart Grid solutions. It is advisable to apply an advanced information architecture based on IEC standards and SOA (Service Oriented Architecture) principles. The applied standards must ensure interoperability in a number of dimensions. Systems integration should commonly employ the standard data model of CIM (Common Information Model). Also the widely accepted standard IEC 61850, used in stations’ secondary circuits and many other applications (distributed generation, wind farms, etc.) should play an important role. The leading role in the standards’ development and rollout is played by the IEC (International Electrotechnical Commission) and NIST (National Institute of Standards and Technology) in the USA. Current priorities in the area of standardisation for Smart Grids include the following: • Wide-Area Situational Awareness • energy storage • distribution grid management • Cyber Security • network communication. Common acceptance of Smart Grids by consumers depends on the development, application, and implementation of legal, regulatory, and technical systems

Special Issue – Smart Grid

Rafał Czyżewski, ENERGA-OPERATOR SA | Adam Babś, Instytut Energetyki Oddział Gdańsk Krzysztof Madajewski, Instytut Energetyki Oddział Gdańsk

giving confidence in protection of consumers’ privacy, while allowing them access to details of their energy consumption. Similar requirements relate to the protection of confidential data of grid operators and other entities. In practice, of crucial relevance will be the distinction between personal and non-personal data. If the processed data is of a technical nature and neither be related to a specific individual nor allow for such individual’s identification, then distribution system operators and other service providers may process such data without prior consent from the consumers. Although the European legal framework concerning data is adequate and there is no need to extend it, some amendments of specific national legislation may still be necessary to take account of some Smart Grid anticipated features [2].

7. BARRIERS TO SMART GRID DEPLOYMENT Implementation of the Smart Grid has been and will be linked with many barriers of a social, legal and regulatory, economic, and technical nature, which include the following [5]: • incompatibility of and instability of regulatory arrangements • large-scale investment and the associated risks arising from unsuccessful investment • uncertainty with regard to standards • rapid obsolescence of technologies • need to prepare staff to implement Smart Grid solutions • social resistance against the deployment of new technologies.

Among these barriers particularly important are the issues related to potential public resistance against the deployment of innovative solutions and the issues arising from necessary changes in the regulatory area supporting the deployment of Smart Grids. ENERGA-OPERATOR SA intends to engage in these two areas in particular, in order to minimize barriers to deployment and to increase the likelihood of implementing postulated solutions.

8. SUMMARY Smart Grids can significantly contribute to the creation of a new strategy for smart and sustainable development and to the accomplishment of European targets for energy and climate. Smart Grids are also a way of meeting the requirements of promotion of energy efficiency, increased activity on the demand side, increased share of renewables and distributed generation, and of transport electrification. Distribution grid operators have a crucial role in the development of the Smart Grid. Implementation of the Smart Grid concept will increase the power system’s flexibility and will allow benefits for all participants in the value chain, from generators, grid operators, service providers, up to end users and society as a whole. Regardless of the implementation of new technologies in the area of Smart Grids, activities related to the expansion of the distribution network must be continued. The new and upgraded infrastructure will be adapted to the requirements of the Smart Grid.

1. ESCO – energy service company.

References 1. The European Council Conclusions of 4 February 2011, available from: http://www.consilium. europa.eu/uedocs/ cms_data/docs/pressdata/PL/ec/119183.pdf. 2. COM(2011) 112/4. 3. ESMIG, http://www.scribd.com/doc/35826660/LandisGyr-Whitepaper-IDIS and SAP, Smart Grids for Europe: http:// www.scribd.com/doc/47461006/12036-NM-Smart-Grids-for-Europe-En. 4. M490 of 1 March 2011, http://ec.europa.eu/energy/gas_electricity/smartgrids/taskforce_en.htm. 5. Wizja wdrożenia sieci inteligentnej w Energa-Operator SA w perspektywie do 2020 roku [Vision of the Smart Grid deployment at Energa-Operator SA by 2020]. 6. Justification for the Energy Law, December 2011. 7. “Mapping & Gap Analysis”, Report by EEGI Member States Initiative, A pathway towards functional Project for distribution grids, January 2012. 8. “The role of DSO on Smart Grids and Energy Efficiency”, A EURELECTRIC position paper, January 2012. 9. “Smart Grids and Network of the Future”, EURELECTRIC Views, May 2009, Ref: 2009-030-0440.

Special Issue – Smart Grid

“The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA

authors | biographies

Adam Babś

Krzysztof Madajewski Gdańsk | Poland

Gdańsk | Poland

Graduated as Master of Science from the Faculty of Electronics of Gdańsk University of Technology. In 1995 he joined the Institute of Power Engineering, Gdańsk Division where he’s been involved in the development and implementation of automatic voltage control in the National Power System. Currently he manages the Institute’s Power System Automation Department.

Sławomir Noske

Grzegorz Widelski

Chief R& D Engineer at ENERGA-OPERATOR SA. Has been employed in the energy company since 1991. Graduate of Poznań University of Technology, Faculty of Electrical Engineering. He completed postgraduate studies in the legal and management field at the Gdańsk University of Technology and MBA management studies, organized by the Gdańsk Foundation for Management Development. In 2006 he was admitted into the Ph.D. program “Diagnosis of medium voltage cable lines with the use of a partial discharge test using the self-damping voltage wave method”.

Director of Property Development Department at ENERGA-OPERATOR SA. Has been employed in the energy company since 1999. Graduate of Faculty of Electrical and Control Engineering at Gdańsk University of Technology, speciality in electric power. He completed postgraduate studies in the field of power distribution system management at his home university. Currently studies in the MBA management course organized by the Gdańsk Foundation for Management Development.

Gdańsk | Poland

Special Issue – Smart Grid

Tomasz Ogryczak

Adam Babś | Krzysztof Madajewski | Tomasz Ogryczak | Sławomir Noske | Grzegorz Widelski

“The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA 1. INTRODUCTION In 2009 ENERGA-OPERATOR SA decided to deploy smart meters. The project’s first stage covers approx. 100,000 measuring devices in three selected locations, which differ in the nature of the electric vehicle charging. One of the areas selected for the deployment is a zone in its prevailing part of urban character, in the northern part of Poland, supplied from a single point of supply (110/115 kV substation Władysławowo). Subject to the assumption, which has to be verified in the course of implementation, that smart metering development and deployment is the first step in Smart Grid development at ENERGA-OPERATOR SA, it was decided to design and deploy Smart Grid (SG). It was a somewhat natural consequence of this choice to locate the project where the smart meters are deployed, i.e. in the Hel Peninsula. Another reason for choosing this location was the need to improve supply reliability indicators in this area, which in the tourist season especially is very sensitive to interruptions in electricity supply, and failure recovery time is then extended due to problems with power emergency teams’ mobility due to road traffic congestion. The main objective of the Smart Grid pilot project in the Hel Peninsula is to check its basic elements and to develop an implementation concept for similar projects across ENERGA-OPERATOR SA. It has been assumed that the scope of the project should include medium and low voltage grids. Subject to checking – by way of practical implementation – are project elements such as: • central part – IT system integrated with SCADA at the Regional Power Dispatch level • telecommunication infrastructure • automation, control, and measuring equipment in MV and LV grids • installation in LV grid of distributed generation such as photovoltaic cells, wind turbines, as well as heat pumps, smart street lighting, and electric vehicle charging stations. The paper presents the scope and results of engineering, and the expected scope of Smart Grid deployment in the Hel Peninsula.

2. DESCRIPTION OF PREPARATORY AND STUDIES In the ENERGA-OPERATOR SA organisation a project team was appointed that would provide programming of the works and assume the responsibility for the proper flow of information and collection of necessary input data. The entire deployment preparatory work was with the Institute of Power Engineering, Gdańsk Division. The preparatory work was phased into three stages. Stage 1: Development of the Smart Grid deployment and operation concept [1], which included: • analysis, quantitative and qualitative assessment of the current condition of the electricity infrastructure, its loads, connected sources and electric vehicle charging and of the telecommunications infrastructure for use in the Smart Grid deployment in the Hel Peninsula. The inventory and assessment included items such as: MV and LV grids (cable and overhead lines, transformer stations, 110/15 kV substation Władysławowo), telecommunication infrastructure, automation and protections, the existing conventional and renewable generation (including the EC Hel and EC Władysławowo cogeneration plants) and load characteristics [6] • review of Smart Grid functional aspects, such as: AMI systems (Advanced Metering Infrastructure) in Border Guard grids, prosumer and active grid, smart buildings, electric vehicles, DER (Distributed Energy Resources), influence on electric vehicle charging: DSM (Demand Side Management , DR (Demand Response) management and control in microgrids, supply reliability and quality improvement, microgrid stand-alone operation • review and evaluation of available telecommunication, IT, manufacturing, measurement, electricity storage and Transmission technologies, and assessment of their applicability in the Smart Grid project • development of project assumptions including a description of the expected grid functionality and a technical and functional concept of the Smart Grid along

Abstract The article presents the current progress and activities planned in the near future in the implementation of The Smart Peninsula, ENERGA-OPERATOR SA ‘s pilot Smart Grid deployment project. In the three stages of the preparatory work and analysis so far completed a detailed inventory has bee n made of the MV and LV grids covered by the project, a project implementation concept has been developed, as well algorithms of the Smart Grid control, and

the algorithms’ simulation model tests have been completed. The preparatory works have been summarised by a project feasibility study. The functionalities and experimental implementation of an island operation involving the EV Władysławowo cogeneration plant have been selected for the deployment, as well as the implementation at ENERGA-TRADE SA of electric vehicle charging power consumption control in DSM/DR programmes.

Special Issue – Smart Grid

Adam Babś, Institute of Power Engineering, Gdańsk Division | Krzysztof Madajewski, Institute of Power Engineering, Gdańsk Division | Tomasz Ogryczak, Institute of Power Engineering, Gdańsk Division Sławomir Noske, ENERGA-OPERATOR SA | Grzegorz Widelski, ENERGA-OPERATOR SA

with specification of new grid infrastructure elements in the Hel Peninsula. Stage 2: Model studies of the grid operation, and development of control algorithms for Smart Grid in the Hel Peninsula [2] • modelling of the existing elements of generation sources, switching devices, and EA infrastructure • modelling of the new grid elements to be deployed in the pilot project implementation • development of control algorithms for Smart Grid in the Hel Peninsula • verification of interoperability of the modelled existing and new grid elements within the Smart Grid • model studies of the grid operation including the Smart Grid application algorithms • development of electricity generation and consumption. Stage 3: Feasibility study for the implementation of Smart Grid project [3] • concept and scope of the Smart Grid project in the Hel Peninsula • project implementation schedule • financial analysis • assumptions for financial analysis, including capital and operating costs and benefits derived from the project • schedule of expenditures • project implementation conditions and analysis of risk factors and critical success factors • external sources of funding for Smart Grid in the Hel Peninsula project.

Special Issue – Smart Grid

The entire preparatory work was completed in 2011 and following discussions and feasibility studies guidelines for implementation were developed [4] which specified the implementation scope broken down by work type (software development, MV and LV grids installation and modernization, DSM programs). These guidelines will provide the basis for the pilot system deployment. The analysis and qualitative assessment of the current power infrastructure condition enabled defining the scope of potential implementation. The power grid that supplies consumers in the Hel Peninsula (Fig. 1) is a radial grid supplied from 110/115 kV substation Władysławowo, which altogether includes more than 450 MV/LV transformation points in fifty localities. The Hel Peninsula is powered from 110/115 kV substation Władysławowo by two 30 kV cable lines and two 15 kV lines. The MV cable lines’ length is over 171 km (sections from 50 to 240 mm 2); 50 km of these are 30 kV lines. The 70 mm2 overhead line is 14.5 km long and includes some cable segments. Altogether in the Hel Peninsula 97 MV/LV transformers are deployed with powers from 63 kVA to 630 kVA. At SP Jurata two 30/15 kV 6.3 MVA transformers and one 15/15kV 10.7 MVA autotransformer are installed. At 110/115 kV substation Władysławowo to a 30 kV substation a cogeneration plant with two 2 x 5.5 MW generators is connected with 30 kV lines. The peak power demand of 10 MW is experienced in July, and the minimum demand of 5 MW in October. The night-time minimum loads are 4 MW and 3 MW, respectively. The MV grid supplies from 3 MVAr to 4 MVAr reactive power.

“The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA

Fig. 1. MV power grid diagram in the Hel Peninsula

3. DESCRIPTION OF SELECTED FUNCTIONALITIES PROVIDED FOR IMPLEMENTATION Described below are the assumptions and algorithms for basic functionalities to be implemented in the Smart Grid pilot deployment in the Hel Peninsula. This functionality will be implemented at the Regional Power Dispatch Gdańsk Branch in a new software known as DMS (Distribution Management System). Functions associated with demand control and electric vehicle charging system support are assigned to the applications that will be deployed on the side of ENERGA – TRADE SA. Implementation of these functionalities will entail necessary provision of the MV and LV grid infrastructure with measurement and control devices, and provision of the electric vehicle charging covered by the DSM/DR programme with actuators controlled by the application deployed at ENERGA-TRADE SA, 3.1. Fault Detection, Isolation & Recovery – FDIR function Implementation of this functionality will enable: 1. Reduced time of after fault recovery in the MV grid, and limited number of consumers deprived of supply during a fault by way of the application of an algorithm of fault location in the MV grid and the grid reconfigu-

ration to the effect of its faulty sections’ elimination 2. Reduced grid failure rate by way of switching gear upgrade in ca. 30% of MV/LV substations 3. Reduced time of after fault recovery in MV grid by way of remote control of switches in the grid 4. Gathered MV/LV substation automation related experience 5. Launched process of the SCADA system upgrade at the Regional Power Dispatch to the extent of MV grid operation management support – DSM module development. The main task of the algorithm of real time MV grid fault location and grid reconfiguration is to isolate the faulty grid section and recovery of supply of the electric vehicle charging that are supplied from not faulty lines. The algorithm utilises the following signals (input data) collected in real time: • status of remotely controlled switches • short-circuit current signals from fault detectors • currents in lines where they are measures • MV/LV transformer powers • MV line loads in 110/15 kV substation/SP (currents, powers) • communication status of remotely controlled devices, • power supply status of controlled devices • protection actuation, tripping at 110/15 kV substation /SP, number of auto reclosure cycles to be performed after emergency line outage

Special Issue – Smart Grid

• automatic recloser activation at 110/15 kV substation/SP (reclosing automation that checks whether a fault is permanent or transient).

Algorithm of MV grid fault area location and grid reconfiguration 1. To check whether the automatic recloser has completed its action at the 110/15 kV substation/SP, where emergency line outage occurred. If the last automatic reclosure cycle has been completed, go to step 2; if not, keep waiting until the automatic reclosure cycle sequence’s completion 2. Identify an operable section of the faulty line: from the power line’s supply at 110/15 kV substation/SP to the most distant MV/LV substation, a register signalling of a fault location has occurred (in a grid layout the distance from a MV/LV substation to a 110/15 kV substation/SP supply source is measured by the total number of the MV/LV substations and the points of disconnector installation outside MV/LV substations located in the section of line between the 110/15 kV substation/SP and the MV/LV substation) 3. In the line section identified in step 2 locate the remotely controlled disconnector, the most distant from the 110/15 kV substation/SP supply source 4. Remotely disconnect the line using the disconnector identified in step 3 5. At the 110/15 kV substation/SP switch on the switched off circuit breaker in the faulted line 6. Identify all line sections from the disconnection point identified in step 3 that have been deprived of supply as a result of the disconnection referred to in step 4. Notify these line sections to the dispatcher 7. Identify the position of the fault locator that detects a short-circuit current and of the detector most distant from the disconnector referred to in step 3 8. From the grid point referred to in step 7, determine all (not supplied) sections up to division points or the grid end 9. In each section determined in step 8 identify the position of the fault locator that didn’t signal a shortcircuit current and in the line section the closest to the grid point determined in step 7. Mark the disconnector position as the end of a new line section. If in a line section there is no fault locator, the section will remain unaltered 10. The fault area includes all line sections identified in step 9. Notify these sections to the dispatcher 11. After the fault location leave to the dispatcher’s discretion selection of the mode of further operation in connection with grid reconfiguration: manual or automatic 12. If the manual mode is selected, go to step 14 13. Notify the dispatcher of the grid division points that are the ends of the line sections determined in step 8. The end of the algorithm 14. For each line section terminated with a grid division point and determined in step 8 identify the disconnector most distant from a division point, but outside a

Special Issue – Smart Grid

section included in the fault area, except the section’s end point. If such a disconnector has been located, disconnect the line (a new division point), close the disconnector in the point of the previous division, and go to step 8. If there is no line section that meets the above conditions (no disconnector that might set a new division point) – the end of the algorithm. The FDIR algorithm formulated above in descriptive form will be so reformulated to operations on matrices that the faulty section will be eliminated and the new configuration determined in fully automatic way [8]. The departure point for such algorithm formulation is the actual layout of grid connections mapped in matrix format (connection matrix L), the vector that describes the shortcircuit current flow and direction (vector G) and a matrix that describes controlled switch positions (matrix Q). The connection matrix L is a square matrix of the size corresponding to the number of branches and nodes in the concerned MV grid area. The elements of this matrix assume the following values: 1  lij =  –1 0 

node i connected to branch i in direction i node i connected to branch i in direction reverse to i node i branch j not connected

Matrix Q that describes the controlled switch positions is a square matrix of the size corresponding to the number of branches and nodes in the concerned MV grid area. The elements of this matrix assume the following values:

1 node i connected to branch i node i branch j q ij =   0 not connected  Vector G, that describes the short-circuit current and its direction with the size corresponding to the number of branches, has the value of 1 in the elements where the short-circuit current was detected. The faulty branch may be identified as the result of the operation of multiplication of matrices G and L, as vector P, in which value 1 will correspond to a faulty branch. Multiplication of matrix Q that describes the controlled switch positions by vector P, results in vector D that indicates the elements – remotely controlled disconnectors, which should be opened to isolate the faulty branch. For example for connection matrix L, switch position matrix Q and short-circuit current vector G, with values:

1 −1 0 L=  0 −1 0  0

0 1 −1 0 0 −1 0

0 0 1 −1 0 0 −1

0 0 0 1 0 0 0

0 0 0 0 1 0 0

0 0 0 0 0 1 0

0 0 0 0 0 0 1 

“The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA

1 0 0 Q = 0 0 0 0

1 1 0 0 0 0 0

0 1 1 0 0 0 0

0 0 1 1 0 0 0

1 0 0 0 1 0 0

0 1 0 0 0 1 0

Ui, min – minimum client supply voltage in supply line i (LV bar voltage in MV/LV substation from which the possible voltage drop between MV/LV transformer and the most distant electric vehicle charging electricity meter) Unom – LV grid nominal voltage.

0 0 1 0 0 0 1

G=[1100000] The result of multiplication of matrices G and L – vector P = G L indicates the faulty branch (value 1 in the second position)

P=[0100000] The result of multiplication of matrix Q and P – vector D = Q P indicates the remotely controlled switches, which should be opened to isolate the faulty branch (values 1 in respective positions).

3.2. Voltage control – IVVC2 function Availability of grid parameter measurements (voltage) in points deep inside MV and LV grids supplied from a transformer with an on-load tap changer enables implementation of a control algorithm that uses these measurements. The applied algorithm of control with voltage line compensation in many supply lines, i.e. MLDC3 algorithm allows considering differentiation of the individual supply line loads and the impact of local generation. The designated transformer ratio (tap changer position) will ensure maintenance of the client supply voltage within allowable limits in all supply lines. This algorithm also ensures reduction of the number of tap changes, at low load rates and low voltage drops. The algorithm uses the objective function being the sum of squared deviations of the minimum and maximum voltage, respectively, in each supply line, from the rated voltage. The minimum and maximum values are determined based on the distribution grid model and measurements taken in the grid at different tap changer positions. The optimization consists in choosing such a tap changer position, at which the objective function reaches its minimum. N

[

J =∑ (Ui ,maks – Unom ) +(Unom – Ui ,min ) i =1

]

where: N – number of lines supplying electric vehicle charging from a 110/15 kV substation Ui, max – maximum electric vehicle charging supply voltage in supply line i (LV bar voltage in MV/LV substation)

Regulation will be carried out by remote setting the voltage setpoint for two regulators of 30/15 kV transformers in SP Jurata. For determination of the voltage regulation setpoints the measurements will be used that have been taken in the SP Jurata station and deep within the grid at six 15/0.4 substation on the LV side. Application of MLDC algorithm enables the implementation of CVR (the function that allows reduction of electric vehicle charging demand for electricity (Conservative Voltage Reduction), which allows reduction of electric vehicle charging demand for electricity. This is one of the types of DR demand control implemented in Smart Grids. CVR function saves energy by lowering the equipment supply voltage, and increases the demand by increasing the voltage. It is important to control the voltage condition throughout the area supplied from a transformer up to end electric vehicle charging. In this way the demand for active power can be reduced by 2% to as much as 3.5% and the demand for reactive power by 4% to 10%, which may translate into energy savings of 1% to 3%. Regardless of the grid voltage control, by using voltage and current measurements in MV grid such a configuration can be found, at which the grid losses will be minimized. This involves a change of the grid split point, i.e. adjustment of the grid division to changing grid loads.

3.3. Advanced supervision of LV grid, including distributed energy sources It is assumed that the following objectives shall be accomplished: 1. Reduction of the time of LV grid’s after fault recovery through monitoring the supply condition of LV outputs of selected MV/LV substations 2. Gathering experience in LV grid monitoring and use of measurement data from AMI system 3. Carrying out tests of equipment and technologies enabling recording of phenomena in LV grids. The advanced supervision of LV grid will consists in extended visual rendering of some LV switchgear in selected MV/LV substation, covering: • signalling of the status (position) of circuit-breakers and fused disconnectors (the main and in outgoing bays) • signalling of blown fuses • transformer load current • voltage at switchgear busbar • current in outgoing circuits (at station where it is monitored). LV grid visual rendering should cover the following data acquired from the AMI system: • voltage at electric vehicle charging to grid connection

Special Issue – Smart Grid

• signalling of lack of voltage at electric vehicle charging to grid connection. It’s been assumed that measurement data can be acquired from the AMI system using of ESB (Enterprise Service Bus – for data exchange within a company via a service bus) and WebServices. The preferred data exchange standard should use a common data model (CIM standard). However, this is dependent on the standard’s implementation in the AMI application system.

3.4. Electric vehicle charging The pilot Smart Grid deployment provides also for the installation of public charging stations for electric vehicles, and of a system of management of these charging stations. It is assumed that the following objectives shall be accomplished: • gathering experience in operation and remote supervision of electric vehicle charging stations • refining the functionality of the pilot system of charging stations management to meet the needs of ENERGA-TRADE SA • promotion of ENERGA capital group as an environment friendly corporation. Two locations of the charging stations were planned at public parking lots near facilities administered by local self-governments, i.e. close to the town hall in Jastarnia and in the town of Hel. A charging station will consist of a master unit and three charging poles. A three-phase 400V AC wiring has been provided for, with the maximum rms current 63 A (43 kW – maximum charge power). A pole will be provided with a standard 400/230V three phase socket and single-phase socket. The poles will be fully controlled by the master unit, so the will be provided with no additional devices such as a controller or meter. The master unit deployed within the parking lot will be responsible for control of the vehicle charging poles. It will be also responsible for communication with the Card Authorisation Centre (CAC) and ENERGA-TRADE. The charging stations management module will be implemented at ENERGA-TRADE. It will be provided with a GSM/GPRS communication module for receipt of information from the charging station and for control of their operation. Charging station monitoring signals will include: • alarm signals – including unauthorized access to station terminal, lock activation • signals related to the charging process – current level of electricity consumption at the station, total electricity input by a client in the transaction. The management system will forward control information to the charging station – the station’s remote switching on and off, and current electricity prices. Information exchanged between a charging station and CAC will allow customer identification based on data retrieved from the customer’s payment card, or denial of customer authorization.

Special Issue – Smart Grid

4. ANTICIPATED SCOPE OF THE DEPLOYMENT The Smart Grid development and deployment concept conceived in the first task, the grid control algorithms, and the grid operation model studies completed in the second task have enabled determining the recommended scope of the experimental Smart Grid system deployment in the Hel Peninsula. The pilot plant will address the following issues: 1. Development and implementation at the Regional Power Dispatch Gdańsk Branch of a distribution grid management software, i.e. Syndis DMS. The following functionality will be implemented through DMS system development: a) fault detection, location, and automatic grid reconfiguration – FDIR b) voltage control c) island operation enforcement. 2. Provision of the MV distribution network in the Hel peninsula with devices and a sensor enabling implementation of selected DMS functions 3. Pilot electric vehicle charging system 4. Deployment at ENERGA-TRADE SA of the DSM management application along with provision of selected electric vehicle charging in the Hel Peninsula with devices enabling implementation of the DSM function – demand and microgeneration management.

4.1. Software works Project of extending the SYNDIS dispatch system at the Regional Power Dispatch in Gdańsk and development of a new SCADA DMS module to the extent of: • connection of new MV/LV substations in the Peninsula with display of remote control, remote measurement, and remote signalling elements in MV and LV grid • CIM-based interface for data exchange with AMI, SID • Syndis-DMS module (FDIR functions, voltage control) • DMS module extension and software. 4.2. Equipment deployment in the Peninsula Upgrade and equipment of MV/LV substations to the extent of: 1. provision of indoor substations with remote control and fault detection equipment – 9 stations • provision of indoor substations with remote control and measuring equipment – 8 stations • provision of uncontrolled indoor substations with fault detectors – 45 stations 2. Deployment of LV switchgear monitoring equipment (10 substations) to the extent of: detailed design, equipment supply and installation, commissioning. 4.3. Island operation including EC Władysławowo cogeneration plant – experiment An experimental project is provided for, including: • separation by switching operations in the MV grid of an area to be supplied from the cogeneration plant in the island operation mode

“The Smart Peninsula” pilot project of Smart Grid deployment at ENERGA-OPERATOR SA

• test of actual island operation of EC Władysławowo cogeneration plant for a selected area that can be supplied from the plant • test results analysis to determine the suitability of EC Władysławowo cogeneration plant’s operation in the Smart Grid area and its interaction with prosumers • development of a scenario of the test of EC Władysławowo cogeneration plant’s island operation involving a Smart Grid section and distributed generation.

4.4. Electric vehicle charging system to the extent of: • development of detailed technical specification for the charging stations and management system, and of system design for two locations • deployment of the charging station in two locations • deployment of the management application at ENERGA-TRADE SA. 4.5. Implementation of power consumption control by electric vehicle charging in DSM/DR programmes Demand and microgeneration management will be implemented at ENERGA-TRADE SA (ETR). The scope of implementation includes: • development of an automatic demand management concept • development and implementation of a demand management application at ETR • deployment of devices enabling DSM function implementation at customers: –– commercial – service customers in tariff group C –– municipal customers in tariff group G –– customers who have chosen to substitute conventional fuels with electricity used for heating (heat pump) –– customers with backup supply lines. As solutions dedicated for active energy consumers will affect the grid operation, it is necessary to coordinate the activities of the system operator and the trading company. The Smart Grid deployment in the Hel Peninsula for control of power consumption by customers will allow accomplishing the following objectives: • testing solutions for management by the trading company of the power output from the grid to consumers and for management of the operation of internal electric vehicle charging (prosumer) microsources connected to the grid • testing solutions for electricity consumption reduction by disconnection from the power grid, at the DSO’s request, of electric vehicle charging with backup supply sources, and covering demand for power with backup Diesel generators or batteries.

5. TELECOMMUNICATION INFRASTRUCTURE Communication with measurement and control devices in the Smart Grid should operate regardless of the MV

grid’s condition, and in particular should be resistant to the grid’s faults such as line-to-earth and line-to-line short circuits and mechanical damage of wires. Communication between MV / LV substations and 110/15 kV substation Władysławowo, using PLC (Power Line Communication i.e. communication that uses power line wires as a communication channel) technology end involving the use of the MV grid, developed and deployed for the AMI project, doesn’t meet the above requirements. Therefore it is reasonable to use a wireless GPRS service-based communication solution for the Smart Grid, independent of the communication used for data transfer in the AMI system, between the grid devices installed at the 110/15 kV substation on the hub installed at a MV/LV substation. If communication in the AMI system between the grid devices installed at the 110/15 kV substation and the hubs installed at a MV/LV substation will be wireless technology (WiMAX, GPRS, CDMA, UMTS, LTE) enabled, then the network can be recommended for use in communication with automatic devices in the MV grid. It is important in this situation that: • at indoor MV / LV substations the network’s terminating devices are installed for the needs of the AMI systems, whereas in overhead switch control points such devices can be installed additionally • telecommunications traffic related to the operation of controllers in the MV grid is significantly smaller than the traffic associated with the AMI implementation, so the network used for AMI can be additionally loaded with traffic related with the MV grid’s automation and it will not deteriorate AMI performance.

6. SUMMARY The pilot Smart Grid deployment in the Hel Peninsula is the first attempt in the Polish power sector at practical implementation and verification of the new Smart Grid related technologies. It is expected that the relatively small scope of implementation, particularly as regards the installation of distributed generation, will allow – after the pilot deployment completion and implementation of the intended functionalities – to gather experiences and draw conclusions as to the future directions of development of such solutions. Of particular interest will be the experience in practical implementation of the fault location and grid reconfiguration algorithms, and of the LV grid monitoring, which will probably result in a noticeable improvement in the grid reliability. Also significant will be the practical experience in the IVVC voltage regulation system’s operation, and the use of its demand control (DR) function. The experimental transition to island operation with the use of the EC Władysławowo cogeneration plant, also planned in the project framework, will allow gathering experience enabling development of the Smart Grid’s island operation including distributed generation and active prosumers. Opportunities will be provided for ENERGA-TRSDE SA to test the efficiency of DSM/DR mechanisms and of the

Special Issue – Smart Grid

management and operation of electric vehicle charging points. Of key relevance for successful deployment of the Smart Grid will be a reliable and fast information transfer network. It will enable quicker identification of faults and their causes, earlier after fault recovery, and ultimately rarer fault occurrences.

Regardless of the implementation of new technologies in Smart Grids, activities related to the distribution grid’s extension must be continued. The new and upgraded infrastructure should be adapted to the requirements of a Smart Grid [5].

1. FDIR – Fault Detection, Isolation & Recovery 2. IVVC – Integrated Volt / Var Control 3. MLDC – Multi Line Drop Compensation

References 1. Opracowanie koncepcji budowy i wdrożenia rozwiązań Smart Grid w sieci ENERGA-OPERATOR SA na Półwyspie Helskim, Etap I, Koncepcja budowy i funkcjonowania sieci Smart Grid [Study of the concept of development and deployment of Smart Grid solutions in the ENERGA-OPERATOR SA grid in the Hel Peninsula, Stage I, Smart Grid development and operation concept], September 2011. 2. Opracowanie koncepcji budowy i wdrożenia rozwiązań Smart Grid w sieci ENERGA-OPERATOR SA na Półwyspie Helskim, Etap II, Przeprowadzenie badań modelowych pracy sieci oraz opracowanie algorytmów sterowania siecią Smart Grid na Półwyspie Helskim [Study of the concept of development and deployment of Smart Grid solutions in the ENERGA-OPERATOR SA grid in the Hel Peninsula, Stage II, Model study of grid operation and development of control algorithms for Smart Grid in the Hel Peninsula], November 2011. 3. Opracowanie koncepcji budowy i wdrożenia rozwiązań Smart Grid w sieci ENERGA-OPERATOR SA na Półwyspie Helskim, Etap III, Opracowanie studium wykonalności realizacji Projektu Smart Grid [Study of the concept of development and deployment of Smart Grid solutions in the ENERGA-OPERATOR SA grid in the Hel Peninsula, Stage III, Feasibility study for Smart Grid project], December 2011. 4. Opracowanie koncepcji budowy i wdrożenia rozwiązań Smart Grid w sieci ENERGA-OPERATOR SA na Półwyspie Helskim, streszczenie, zakres prac – wytyczne realizacyjne [Study of the concept of development and deployment of Smart Grid solutions in the ENERGA-OPERATOR SA grid in the Hel Peninsula, summary of the studies – implementation guidelines], February 2012. 5. Wizja wdrożenia sieci inteligentnej w ENERGA-OPERATOR SA w perspektywie do 2020 roku [Vision of the Smart Grid deployment at ENERGA-OPERATOR SA by 2020], September 2011. 6. Babś A., Smart Grid Hels peninsula pilot project in DSO Energa network – ideas and application, Conference Smart Metering Central and Eastern Europe 2011, Warsawa 17–18 May 2011. 7. Noske S., Widelski G., W kierunku Smart Grid – pilotażowy projekt “Inteligentny Półwysep”, [Towards Smart Grid – “The Smart Peninsula” pilot project] Acta Energetica nr 3/2011. 8. WANG Hui et al., A Fault Detection and Isolation Algorithm for Distribution Systems containing Distributed Generations, Paper No. 1760, APAP Conference, Beijing, October 2011.

Special Issue – Smart Grid

Selected results of simulation studies in “The Smart Peninsula” project

authors | biographies

Andrzej Kąkol

Ksawery Opala

Graduated in Automation and Robotics from the Faculty of Electrical and Control Engineering at Gdańsk University of Technology. Works in System Analyzes Team of Automation and System Analyzes Department at Institute of Power Engineering, Gdańsk Division His interests include dynamics, protections.

Graduated as Master of Science from the Faculty of Electrical and Control Engineering at Gdańsk University of Technology (2001). Now an assistant researcher at Institute of Power Engineering, Gdańsk Division. His area of scientific interest include: ARNE and ARST automated control, areal voltage and reactive power control, EE network operation condition analysis, and flow calculations.

Gdańsk | Poland

Special Issue – Smart Grid

Gdańsk | Poland

Andrzej Kąkol | Ksawery Opala

Selected results of simulation studies in “The Smart Peninsula” project 1. INTRODUCTION In the implementation of “The Smart Peninsula” project a computational model was developed of the MV grid and a fragment of the LV grid in the Hel Peninsula. Individual grid elements, i.e. HV/MV/MV and MV/LV transformers, MV lines, and generators were modelled based on data gathered in inventory taking. Loads were modelled as aggregated loads connected to LV switchgear and control gear assembly of a MV/LV substation. Based on measurements four characteristic profiles were identified of daily demand with the maximum and minimum demand in July and October, respectively. Based on measurement at 110/15 kV substation Władysławowo that supplies the peninsula grid, load profiles were developed for each SP in the Hel Peninsula. These profiles were then entered to the MV grid model, in which points of division were also modelled. For the purpose of dynamic simulations the model was supplemented by control systems: excitation and turbine controller. Numerous simulation studies were performed on the prepared model. They were primarily meant to verify the efficiency of the algorithms proposed in the project. Due to the number of the tested algorithms, and the breadth of their description this paper presents the results of two simulation studies: of MLDC (Multi Line Drop Compensation) voltage control algorithm, and of the Hel Peninsula grid transition to island operation

2. MLDC VOLTAGE CONTROL ALGORITHM MLDC algorithm calculates the voltages in individual grid nodes in a flow programme based on the grid model. For estimation of load supply voltages, as a function of the voltage at SP, calculation of the power flows is required [1, 2]. In another approach the available off-SP measurements may be directly used, provided that the voltage drops at load connection points are proportional to the loads’ active powers.

Therefore, complete resignation of distribution model was assumed, and the algorithm was based on a large number of measurements and on a historical database. In the currently used HV/MV transformer controllers voltage is measured at the lower bus bars of the MV switchgear in a HV/MV substation, where almost always any MV grid’s voltage is the highest. It was assumed that the new control algorithm should monitor the voltage condition throughout the distribution grid based on measurement in selected locations. Using engineering expertise (knowledge of the grid structure) the measurement points were selected so that they were only a few in the distribution grid’s most sensitive areas. In contrast to the classical method, in MLDC method the transformer tap selection aims at direct determination of the transformer tap number, with which the load supply voltages will stay within allowable limits in all lines. The simulation studies of the MLDC algorithm were performed for 30/15 kV SP Jurata substation and the MV grid supplied (Fig. 1). Objective function J for current tap Z (measurement from the tap changer in the transformer at SP Jurata) is calculated based on voltage measurements:

J = (UPZ_Ju −Uzad )2 + (U95336 −Uzad )2 + (U90720 −Uzad )2+ 2

2 + (U90447 −Uzad ) + (U90436 −Uzad ) + (U90650 −Uzad )

where: Uzad – voltage set point maintained in MLDC algorithm UPZ_Ju – voltage at 15 kV switchgear in SP Jurata Ui – voltage at 15 kV switchgear in selected MV/LV substation i = {95336,90720, 90447, 90436, 90650}. The algorithm calculates the objective function J for the taps in the vicinity of the current tap Z: [Z-3], [Z-2],

Abstract “The Intelligent Peninsula” project implementation required the development of a computational model of a medium voltage grid and of a section of a low voltage grid in the Hel Peninsula. The model was used to perform many simulation analyses in the MV grid. The analyses were used to develop MV grid operation control algorithms. The paper presents results

of the analyses aimed at verification of a MLDC method-based voltage control algorithm. The paper presents results of the analyses aimed at verification of EC Władysławowo cogeneration plant’s suitability for standalone operation in the Hel Peninsula.

Special Issue – Smart Grid

Andrzej Kąkol, Institute of Power Engineering, Gdańsk Division Ksawery Opala, Institute of Power Engineering, Gdańsk Division

MLDC algorytm algorithm

MLDC

control sterowanieo

y a m o p

15 kV

30 kV

JPORT 90720

HELLESNA 90436

HELX 90447

HELZATOK 90514

GPZ Władysławowo

TR1

HELKORMR 90448

JPAŻYCA 95336

PZ Kuźnica

HELPIHM 90446 HELELEKT 90650 PZ HEL 9008

TR2

SP PZJurata Jurata Fig. 1. Functional diagram of the MLDC algorithm implementation at SP Jurata

[Z-1], [Z+1], [Z+2], [Z+3]. If tap Z* is found, for which the objective function amounts for less than J for the current tap Z, the algorithm shall generate a new set point – tap Z*.

2.1. Algorithm implementation mode The SP Jurata operating condition was adopted based on the inventory data (SCADA diagram of MV grid – Wejherowo region) gathered in the project implementation course. The data shows that the substation is supplied by the 30 kV line from 110/15 kV substation Władysławowo. The 30 kV line from SP Kuźnica is switched off at one end. At SP Jurata TRI transformer supplies the 15 kV bus bar systems connected by a coupler. The substation supplies the 15 kV grid from Jastarnia up to Hel. For the analysis MV grid models had been prepared with 96 15-minute load conditions and the supply from SP Jurata. Each model reflects the course of P and Q demand in receiving nodes on a specific day. • For each of the 96 conditions the dependence was determined of the voltage changes in selected MV/LV substations on the tap change within the scope <Z min , Z max >. • Then for each of the 96 conditions calculations were made with the voltage control active at the 15 kV bus bars in SP Jurata. The classical instance of MV grid voltage control: voltage set point U d = 15.8 kV, dead band ε = 300 V. • In the next step calculations were made for the 96 operating conditions taking into account the MLDC controller’s operation with the objective function J and the control implementation as the optimal tap Z*. • The results obtained of the classical and MLDS controllers’ operation were then compared .

Special Issue – Smart Grid

• Conclusions drawn from the comparison were used to implement the modifications described in a further part of this study. • In the charts presented below the Y axis is scaled from 1 up to 97. These points correspond to 15-minute conditions of the analysed grid. The chart consisting of 97 conditions corresponds to the daily course of a given variable.

2.2. Comparison of the classical and proposed MLDC algorithms To ensure reliability of comparison of the both algorithms outcomes, the same voltage set point Uzad = 15.8 kV was adopted. As shown below (Fig. 2), the MLDC algorithm’s impact proven to be below expectations. The voltage at 15 kV switchgear in SP Jurata was, in around half of the conditions, below that maintained by the classical controller. It transpired that despite the choice of measurement points in terminal locations of the grid supplied by SP Jurata, the voltage drop for them turned out to be negligible. Therefore tying up, through the objective function, all points by set point Uzad had resulted in stronger voltage correlation with value 15.8 kV that in the case of the classical controller with dead band ε = 300 V. Change in measurement point locations The results of the both algorithms’ comparison enforced modification of the MLDC algorithm. The formulation of J objective function was not questionable, whereas doubts inspired the measurement point locations. First and foremost it was decided that measurements should be taken at the 400 V switchgear of a MV/LV substation rather than, as previously, at 15 kV bus bars. In

Selected results of simulation studies in “The Smart Peninsula” project

SP_Jurata_15 KV

Classical_control MLDC_15kV

Fig. 2. Levels of 15 kV voltage at SP Jurata with classical and MLDC regulations

SP_Jurata_15 KV

MLDC_0.4 kV Classical_control

Fig. 3. Levels of 15 kV voltage at SP Jurata with classical and MLDC_0.4 kV regulations

Special Issue – Smart Grid

Andrzej Kąkol, Institute of Power Engineering, Gdańsk Division Ksawery Opala, Institute of Power Engineering, Gdańsk Division

Voltage in Hel_Morska_LV node

MLDC_0.4 kV Classical_control

Fig. 4. Levels of 400 V voltage at Hel Morska substation with both regulation modes

Tap No.

Classical delta MLDC_0.4 kV

Fig. 5. Tap changer position at SP Jurata with classical control and MLDC_0.4 kV with dead band

Special Issue – Smart Grid

Selected results of simulation studies in “The Smart Peninsula” project

addition, the fact was taken into account that the voltage drop at MV/LV transformer is not ruled by its distance from SP Jurata, by the transformer’s load of P and Q powers. Therefore, nodes were selected on the lower side of MV/LV transformers with permanently lower voltages. Measurements in these nodes had replaced those previously used in the J formula. The results of stimulation with the new measurement points are presented below. Fig. 4 presents voltage levels at Hel Morska node, where voltage is the lowest of those on the lower sides of MV/LV transformers in the grid supplied by SP Jurata. This figure, as well as Fig. 3, show benefits from the MLDC algorithm application. It allows maintaining voltage in the grid at a level beyond the usual one with no excesses over allowable values in either 15 kV, or 400 V grids. Adoption of the modified MLDC algorithm had brought about the expected outcome.

Dead band application However, the algorithm in this form brings about an adverse effect of more changes compared to the classical control. The difference is two changes a day, which accounts for approx. 17% of the daily number of changes. In order to eliminate the excessive number of changes under the MLDC algorithm control a dead band was applied to the objective function J. Owing to this the number of changes was reduced, and the evident capacity to shape the voltage profile was nevertheless retained. Of course, the scale of impact on the voltage level in 15 kV and 400 V grids decreases as the dead band increases.

Below in Fig. 5 the effect of dead band application is shown. The dead band was selected so as to provide a compromise between voltage control and reduction of the number of changes. The daily number of changes was reduced by 17% compared to the classical regulation.

Reduction of the number of measurement points and voltage lowering The last step in the model studies was to check the manner of voltage lowering and the possible option of reduction of the number of measurement points in the 400 V grid. The idea to reduce the number of measurement points is connected with lowering the algorithm implementation cost. Given the MLDS algorithm’s use for controlled voltage raising and lowering, the following assumption was adopted: voltage raising the constraints are attributed to the nodes, where voltages are the highest, and the most sensitive are the nodes with low voltage. The exactly reverse assumption refers to voltage lowering: voltage lowering is constrained by the nodes with low voltage, and the most sensitive to change of Uzad are the nodes with high voltage. Therefore the measurement point locations were reverified and the following nodes were selected: • 15 kV switchgear in SP Jurata substation • Hel Morska LV and Jurata Treatment Plant LV – nodes with the lowest voltage level • Hel_Bór_nn – the node with the highest voltage level.

SP_Jurata_15 KV

MLDC_0.4 kV_3p Classical_control

Fig. 6. Effect of the function of lowering voltage at SP Jurata 15 kV in relation to the classical control

Special Issue – Smart Grid

Andrzej Kąkol, Institute of Power Engineering, Gdańsk Division Ksawery Opala, Institute of Power Engineering, Gdańsk Division

Voltage in Hel_Morska_LV node

MLDC_0.4 kV_3p Classical_control

Fig. 7. Effect of the function of lowering voltage at Hel Morska 400 V node in relation to the classical control

The stimulations had confirmed the effectiveness of the MLDS algorithm’s operation based on three measurement points deep inside the grid located on 400 V level. Voltage characteristics under controlled grid voltage lowering are presented below (Fig. 6, 7).

2.2.1. Conclusions The stimulation studies of the MLDC voltage control algorithm provided a wealth of valuable information. It was used to modify the algorithm’s original version. The major modifications included: • algorithm basing on measurements from points located deep inside the grid on the lower sides of MV/ LVV transformers, • new selection manner of measurement node locations – representation of the nodes with the highest and the lowest voltage levels, • the MLDC algorithm application enforces application of a dead band for the objective function J in order to reduce the number of changes. When the above modifications had been implemented, satisfactory results were finally obtained. Another relevant to operations dispatch information is that the set point in the MLDC controller doesn’t warrant that the allowable voltages will not be exceeded. Active locks should be added to the algorithm that cancels the tap changer control toward excess of the upper of lower allowable limit. In the course of the stimulations the locks played a significant role reducing changes that would otherwise

Special Issue – Smart Grid

result from consideration of the J objective function value only

3. ISLAND OPERATION “The Smart peninsula” project concept provided for adjustment of the MV grid supplied from 110/15 kV substation Władysławowo to standalone operation. According to the assumptions adopted at the study’s outset, the island operation was to be implemented with use of renewable energy sources (RES) in the Hel Peninsula. Feasibility analysis of RES sources’ connection to the MV and LV grids had shown that no electricity sources with capacity sufficient for the test of a grid fragment’s standalone operation can be installed. Therefore it was decided to develop a concept of the Hel Peninsula island operation with use of the synchronous generator installed at EC Władysławowo cogeneration plant owned by Energobaltic sp. z o.o.

3.1. EC Władysławowo cogeneration plant substation EC Władysławowo cogeneration plant substation is connected with the 30 kV switchgear of MSP Władysławowo substation by two 240 mm2 cable lines, each 2.5 km long. There are two MV substations (30 kV and 11 kV) in EC Władysławowo. The EV Władysławowo 30 kV substation is a double busbar switchgear, and connected to it are (besides the two 30 kV cable lines) two 33/11 kV transformers, 8 MVA and 16 MVA, respectively. The 8 MVA transformer connects the 30

Selected results of simulation studies in “The Smart Peninsula” project

Fig. 8. EC Władysławowo cogeneration plant substation diagram

kV substation with the first busbar of the 11 kV substation marked with BBA symbol, while the 16 MVW transformer connects the 30 kV substation with the second busbar of the 11 kV substation marked with BBB symbol. To the 11 kV BBA busbar a 1 MVA auxiliary transformer (BFT10) and turbo-generator set No. 1 (MKA10) of apparent power 6.75 MVA are connected. To the 11 kV BBB busbar a 1 MVA auxiliary transformer (BFT20) and turbo-generator set No. 2 (MKA20) of apparent power 6.75 MVA are connected. Fig. 8 presents a diagram of the EC Energobaltic substation with turbo-generator sets connected. The Energobaltic cogeneration plant’s summary auxiliary power amounts to ~0.2 MW. The turbo-generator sets in EC Energobaltic cogeneration plant are driven by gas turbines (CX 501 KB7). The gas turbines have been installed by Centrax, while the generator installed in the set has been manufactured by Leroy Somer. The turbines installed at EC Władysławowo cogeneration plant are double-fuel fired, the energy source can be oil. The turbine’s active electrical power at 10°C amounts to 5.5 MW (6 MW at 0°C and ~4.5 MW at 30°C). According to information provided by EC Władysławowo the current active power control set point is 1 MW/ 3 mins (according to EC Władysławowo the maximum set point is 100 kW/s, although with no guarantee of the turbine’s integrity). Whereas the turbine’s start-up from 0 MW up to the rated power takes ~15 mins.

3.2. Model studies completed In their current condition neither EC Władysławowo cogeneration plant substation, nor the MV grid supplied from 110/15 kV substation Władysławowo are suitable for standalone operation. It was assumed for the model studies that all constraints had been removed. The universal gas turbine model and GAST-type active power control system were used in the analyses. 3. The active power control system had been modified by adding integrating element PI 4. Due to the absence of the turbine’s and control system’s operating details; standard parameters were used for the analyses. The operability of the turbo-generator sets installed at EC Władysławowo was analysed for various levels of the Hel Peninsula grid demand. Calculations were made for two grid variants, i.e. complete model of complete structure of the MV grid in the Hel Peninsula, and simplified model with aggregated loads from the entire Hel Peninsula connected to the 30 kV busbar at EC Władysławowo substation. As mentioned above, it was necessary to carry out the simulation to analyse EC Władysławowo’s operation in the event of its transition to island operation. The simulations studies were aimed at: • analysis of P and PI type angular speed control systems’ performance (simplified model) • calculation variant, whereby in the course of island operation the power received by loads in the modelled grid is changing, simulations on the simplified and complete models.

Special Issue – Smart Grid

Andrzej Kąkol, Institute of Power Engineering, Gdańsk Division Ksawery Opala, Institute of Power Engineering, Gdańsk Division

3.2.1. Comparison of PI and P turbine power controllers performance Simulations for the discussed variant were carried out using the simplified grid diagram (as in Fig. 8). Generators MKA10 and MKA20 initially generate power P = 3 MW and Q = 1 MVAr, whereas loads receive P = 4 MW and Q =1 MVAr and P = 4.73 MW and Q =1 MVAr, respectively. The charts below show two simulation versions, one with proportional controller, the other with PI type controller. a)

Fig. 9. Frequency at the busbar of EC Władysławowo substation during the transition to island operation under a) P and b) PI type speed control

Under the P type control after the transition to island operation a permanent error occurs, i.e. frequency sets below its rated value (Fig. 9a). The PI controller reduces the frequency control error to zero.

3.3. Change in power received by loads in the modelled grid This calculation variant shows a case also for the simplified grid diagram and PI type controller, whereby in the stimulation’s 25 second the loads’ active and reactive powers are subject to linear reduction (for 30 s) to 50% of their initial values. Generators MKA10 and MKA20 initially generate power P = 3 MW and Q = 1 MVAr, while the loads receive P = 4 MW and Q = 1 MVAr and P = 4.73 MW and Q = 1 MVAr, respectively.

Special Issue – Smart Grid

Fig. 10. a) EC Energobaltic active power output and b) frequency after the transition to island operation and linear change in the load in separated area

The voltage and turbine control set points - as in the previous calculation variant. Fig. 10a shows changes in the active power output at the transition to island operation (t = 0) and at the change in demand. Fig. shows the rated frequency’s recovery after a transient frequency increase over 50 Hz.

Selected results of simulation studies in “The Smart Peninsula” project

3.4. Conclusions Analyses have been concluded aimed at verification of EC Władysławowo’s suitability for standalone operation. Due to unavailability of data required for the model the stimulations were carried out using the turbine parameters of a unit of similar power. The results indicate that EC Władysławowo can be adjusted to standalone operation. It should be underlined that for the final assessment of EC Władysławowo’s controllability at standalone operation the actual parameters of the generator units should be used.

4. SUMMARY Numerous simulation studies completed in the “The Smart Peninsula” project implementation enabled verification of the adopted control algorithms’ correctness. It may be unambiguously declared based on the MLDC

algorithm tests that the voltage observability in selected LV grid nodes enables implementation of new functionalities. First of all, unrestricted shaping of the voltage profile is feasible, which consists in controlled (subject to consideration of the range of allowable voltages) raising or lowering the voltage at load supply. Of particular interest is the possibility of lowering CVR voltage with a view to savings, which allows practically cost-free mitigation of the effects of daily peaks of demand in MV and LV grids. Also, the analysis of EC Władysławowo’s controllability at island operation allows assuming that the cogeneration plant could be operated in a standalone grid in the Hel Peninsula. Of course, to enable such function of EC Władyslawowo plant necessary modifications would be required with regard to generator voltage control and island operation automatic detection.

References 1. Joon-Ho Choi, The Dead Band Control of LTC Transformer at Distribution Substation, IEEE Transactions on Power Delivery, vol. 24, no. 1, February 2009. 2. Baran M.E., Ming-Yung Hsu, Volt/Var Control at Distribution Substations, IEEE Transactions on Power Delivery, vol. 14, no. 1, February 1999. 3. Massucco S., Pitto A., Silvestro F, A gas turbine model for studies on distributed generation penetration into distribution networks, IEEE Transactions on Power Systems, vol. 26, no. 3, August 2011. 4. Mahat P ., Chen Z., Bak-Jensen B., Gas turbine control for islanding operation of distributed systems, IEEE 2009, Power & Energy Society General Meeting PES ’09.

Special Issue – Smart Grid

Comprehensive automation and monitoring of MV grids as the key element of improvement of energy supply reliability and continuity

authors | biographies

Stanisław Kubacki

Jacek Świderski

Director of Grid Assets Management ENERGA-OPERATOR SA. Graduated from Faculty of Electrical Engineering of Wrocław University of Technology and from postgraduate studies: Economic Calculation and Management, Organization and Management for Managerial Staff, Operation of Power Systems, Energy Market, Distributed Generation, and E-infrastructure in Municipalities. He has gained significant experience from many years of work in management positions, including at Słupsk Electricity Board in the Northern Electricity District. Former Chairman of the Board of Słupsk Electricity Board S.A. Former CEO of ENERGA SA.

Graduated from the Faculty of Electronics of Gdańsk University of Technology (1974). He was granted the Ph.D. degree at the Faculty (1982). An assistant professor at the Department of Control and Data Communications of the Institute of Power Engineering, Gdańsk Division. His professional interests are related to the issues of telecommunications and ICT in the power sector. To this extent he has been involved in expert and teaching work. Author of numerous national and international publications and papers. A member of IEEE Institute of Electrical and Electronics Engineers, SEP Association of Polish Electrical Engineers, and PTETiS Polish Society for Theoretical and Applied Electrical Engineering.

Gdańsk | Poland

Marcin Tarasiuk Gdańsk | Poland

Graduated from the Faculty of Electrical Engineering and Automation of Gdańsk University of Technology (1997). Deputy Manager at the Department of Control and Data Communications of the Institute of Power Engineering, Gdańsk Division. His professional interests are related to the implementation of modern technologies in the area of distribution grid supervision and control, and applications of microprocessor technology in automation systems in power engineering. He also studies the issues of data transfer in the power system, and the applications of PN-EN 61850 standard. He has been involved in training activities in this field.

Special Issue – Smart Grid

Gdańsk | Poland

Stanisław Kubacki | Jacek Świderski | Marcin Tarasiuk

Comprehensive automation and monitoring of MV grids as the key element of improvement of energy supply reliability and continuity 1. INTRODUCTION The European Union legislation and the operations of the electricity market regulators in European countries confront the actors in the power sector with new tasks involved in achieving such objectives as: increased reliability and continuity of energy supply, increased energy efficiency, development of distributed generation including renewable energy sources, and energy consumers’ active role in shaping demand. The Smart Grid concept should facilitate the achievement of these objectives. The key element of the Smart Grid concept in the area of the distribution grid is the assurance of controllability (automation) and observability (monitoring) of medium voltage (MV) grids. Currently, the monitoring, control and data collection functions are performed in the MV distribution network to a small extent and they mainly refer to HV/MV transformation points. The Smart Grid concept envisages the implementation of remote control and monitoring in selected points deep inside MV grids, and the automation of processes so far performed by the dispatcher and power emergency teams. Such selected MV grid points include supply points (SP), switching substations (SS), cable connectors (CC), pole switches, and MV/LV transformer stations. MV grids automation and monitoring will support the following processes and functions: • automated switching in MV grids • secure use of the existing grid infrastructure during normal operation and at failure repair, using the current load and load before failure data • network expansion planning based on current load data • MV power flow calculation • loss optimisation • short-circuit power calculation • voltage control • normally open point locations optimisation

• selection of additional electricity source point connection locations to enable electricity loss reduction. One of the main goals of MV grid automation and monitoring is to improve the reliability of electricity supplies to consumers. Reliability of supply, defined as the ability to ensure supply continuity, is measured by several indicators, such as: SAIDI (System Average Interruption Duration Index) – a measure of the average long (up to 12 hrs) and very long (up to 24 hrs) power failure duration, SAIFI (System Average Interruption Frequency Index) – a measure of the average long and very long power failure interval, MAIFI (Momentary Average Interruption Frequency Index) – a measure of the average short power failure interval. The Polish legislation obligates the distribution system operator (DSO) to the public disclosure of the above indicators [7]. In many European countries these indicators are used by energy market regulators to model distribution company revenues. From the supply reliability viewpoint a key MV grid automation element is the automation of switching in the MV grid and fault detection and location. Widespread deployment in MV grids of fault monitoring systems with communication to the dispatcher centre, and of remotely controlled switches, associated with comprehensive automation and grid monitoring will allow the quick fault detection, separation of the faulty segment, and the supply recovery for some recipients, which will significantly reduce the SAIDI and SAIFI indices.

2. GRID OBSERVABILITY The grid observability concept should be perceived as grid monitoring to an extent sufficient to assess its condition from the DSO dispatcher level. Measurement data should be fed to the SCADA system in real time,which must be understood as a time shorter than the required response. The following parameters, should be monitored from the SCADA level: • active and reactive power loads of grid nodes

Abstract The paper presents the issue of comprehensive automation and monitoring of medium voltage (MV) grids as a key element of the Smart Grid concept. The existing condition of MV grid control and monitoring is discussed, and the concept of a solution which will provide the possibility of remote automatic grid reconfiguration and ensure full grid observability from the dispatching system level is introduced. Automation of MV grid switching is discussed in detail to isolate a faulty line section and supply electricity at the time of the failure to the largest possible number of recipients.

An example of such automation controls’ operation is also presented. The paper’s second part presents the key role of the quick fault location function and the possibility of the MV grid’s remote reconfiguration for improving power supply reliability (SAIDI and SAIFI indices). It is also shown how an increase in the number of points fitted with faulted circuit indicators with the option of remote control of switches from the dispatch system in MV grids may affect reduction of SAIDI and SAIFI indices across ENERGA-OPERATOR SA. divisions.

Special Issue – Smart Grid

Stanisław Kubacki, ENERGA-OPERATOR SA | Jacek Świderski, Institute of Power Engineering, Gdańsk Division Marcin Tarasiuk, Institute of Power Engineering, Gdańsk Division

• phase voltages and currents • grid switch statuses • protection trippings • fault location details • details of distributed generation output, generation unit statuses, and distributed generation forecasts [6]. MV grid observability improves the quality of power flow calculations. The actual measurement data from the MV grid’s key nodes, in conjunction with the measured data obtained from the AMI (Advanced Metering Infrastructure) system enable verification of the assumptions adopted for calculations. Adoption of the actual loads for calculations leads to more accurate and reliable results and facilitates making the best decisions with regard to operational planning (grid layout, planned outages) and to investment processes in MV grids. Measured data helps to identify the grid normally open point locations that are optimal from the point of view of minimizing losses (they may vary depending on season or time of day), and facilitate selection of such MV grid locations for connecting additional electricity sources or storages, which allows reducing energy losses. Currently MV grid observability is provided by monitoring the currents, voltages, active and reactive powers, and the statuses of switches in the MV switching bays of HV/MV substations. No power flows and voltage levels (except in a few cases) are monitored deep inside grids. Voltage may be measured in selected MV grid points by independent measuring systems or by AMI balancing meters deployed at transformer stations. Where balancing meters are used, voltage is measured at the transformer’s low side. For quick detection of fault locations the widespread deployment of earth and poly-phase fault indicators with remote communication to the dispatcher centre is necessary. The quick fault location function along with the option of remote MV grid reconfiguration is of key relevance to the improvement of power supply reliability (SAIDI and SAIFI indices). The fault detection function can be implemented in the current and voltage measuring systems installed in MV grid nodes, or in dedicated earth or poly-phase fault indicators. Locations of remotely transmitted measurements are primarily determined by the concerned MV grid’s topology and operational experience. Therefore, measuring devices should be deployed in the locations indicated by operation services. The dedicated faulted circuit indicator should be installed mandatorily in all places where remotely controlled switches are deployed. Increasing the MV grid monitoring scope is becoming necessary. Power companies that have taken steps in this direction indicate that this brings about substantial benefits [5, 6].

3. AUTOMATED SWITCHING IN MV GRIDS The option of MV grid quick reconfiguration and separation of a faulty grid segment is the basic Smart Grid functionality. A faulty grid segment can be separated by local automatic controls (reclosers), areal control (from

Special Issue – Smart Grid

the HV/MV substation level), or centralised remote control from the SCADA system level at the dispatching centre that manages the MV grid. Centralised control enables the implementation of more complex switching algorithms and gives the dispatcher a greater possibility of quick intervention. The disadvantage of centralized control is the need for an extensive communication system, and the sensitivity to faults in the system. It will be possible to achieve the new Smart Grid concept specific objectives only with the application of centralised monitoring and control that enables the implementation of complex control functions and data analysis to be implemented within the Smart Grid deployment. Remote control of switches in MV grids from the central system level is designed to isolate a faulty MV grid section and to ensure electricity supply to as many recipients as possible. The following three advancement levels of automatic controls that perform this task may be distinguished: 1. manual control by dispatcher 2. dispatcher control with proposed switching sequence 3. automatic control (without human intervention). All these levels assume the presence of fault detection systems in the remote control locations, and the use of this information in the process of faulty MV grid section isolation. The first level assumes that the decision on switching locations and sequence is made by the dispatcher based on information from the line load and fault monitoring systems, and on the dispatcher’s expertise. The second level involves in fact the deployment of a complete automated switching system lacking only the feedback, that is dispatcher-independent delivery of the control sequence. At the moment the system detects a fault in the MV grid, a switching sequence proposal is generated. It is up to the dispatcher which switching is actually executed. The third level of automation, whereby switching operations are performed automatically without the dispatcher’s contribution by a respective module of the SCADA system, ensures the maximum improvement of the supply reliability indices, and should eventually be implemented in the dispatcher system. Since such fully automatic controls perform highly responsible functions, it is advisable to precede the third level implementation with implementation of the second level with dispatcher control over switching execution. It is also necessary to implement a mechanism that blocks off the automatic operation (at the dispatcher’s command) and the transition from third level to the first or second level described above. A system of automatic isolation of a faulty MV grid section should have the following characteristics: • autonomy – upon detection of a fault (e.g. short circuit) in a MV line the automatic controls will issue an appropriate warning to the dispatcher, and will perform switching in the MV grid to restore power supply to as many recipients as possible, and then they will generate a report of the performed actions for the dispatcher

Comprehensive automation and monitoring of MV grids as the key element of improvement of energy supply reliability and continuity

• safety – the automatic controls cannot perform any operation that will cause danger to human life and health (e.g. to power emergency personnel working in the grid) • adaptability – each change in the grid configuration, i.e. switching the grid at the dispatcher’s order or triggered by a protection and/or an automatic control, shall automatically adjust the automatic controls’ parameters to the new conditions; no communication with field devices will also alter the system configuration accordingly • scalability – the possibility of system expansion, i.e. of adding more elements that implement automatic control in new areas of the grid. The scope of information necessary for proper operation of such automatic controls include the following: • information about the occurrence of an earth or polyphase fault, the source of which is a dedicated faulted circuit indicator installed in a control point, or a measurement system provided with a fault detection algorithm • status of switches in MV grid (grid status) • status of communication with each radio-controlled switch • remote control outages at field controllers • current and allowable line loads and, in justified cases, individual line segment loads • details of works executed in MV grid. In general this information should be obtained from the dispatcher system and from associated systems. An example of automatic control operation is presented in the subsequent drawings. Fig. 1 shows a grid segment comprising two lines L1100 and L1200, that connect three HV/MV substations: GPZ1, GPZ2 and GPZ3. The lines branch off into radial lines L1101, L1102, L1103, L1201 and L1202. At all stations TR1…,TR5 installed are MV switches Q2…, Q11 i

Q13…, Q19 and faulted circuit indicators c2…, c11 i c13…, c19. At the HV/LV substations (GPZs) installed are MV circuit breakers (Q1, Q12, Q20) and automatic protections that perform the short-circuit protection function (c1, c12, c20). TR stations facilitate 15/0.4 kV transformers that supply local recipients. The current open point is implemented by switches Q3 and Q13, while in general the switches do not have to be normally open points (e.g. resulting from the smaller loss criterion). A fault may appear in any line section marked from a to l. Fig. 1 also shows a potential fault in the line section marked with letter e. Faulted circuit indicators c9, c11 and protection c12 are activated. Upon the opening of circuit breaker Q12 at GPZ2 recipients supplied from stations TR2 and TR3 are deprived of the supply. In order to isolate the faulty grid section it is necessary to open switches Q7 and Q9. Upon the closure of switch Q12 remain the recipients not supplied connected to station TR2. Therefore, there is the need to close one of the switches Q3 or Q13. Since line L1100 has been faulted, and the line’s open point is at switch Q3, this switch will be closed. In special cases (danger of overloading part of the grid) the automatic controls can perform the closure of switch Q13 as the most beneficial action. The grid layout after the automatic control action is shown in Fig. 2. All recipients are supplied. No recipient was deprived of the supply for longer than the following operations required: • delayed response in case of transient faults (auto-reclosure in overhead lines) • switching algorithm determination • switching sequence execution (with delays in signal and control response transfers). This duration should not exceed three minutes (short interruption).

Fig. 1. Example MV grid -– the fault appears in section e

Special Issue – Smart Grid

Stanisław Kubacki, ENERGA-OPERATOR SA | Jacek Świderski, Institute of Power Engineering, Gdańsk Division Marcin Tarasiuk, Institute of Power Engineering, Gdańsk Division

4. IMPROVEMENT OF SUPPLY RELIABILITY INDICES SAIDI index of the average duration of long and very long interruption, denominated in minutes per recipient per year, and equal to the sum of the products of the duration and the number of recipients exposed to the duration effects during the year, divided by the total number of supplied recipients:

∑ r ×N i

(1) = i SAIDI

SAIFI index of the average system frequency of long and very long interruption, equal to the number of the recipients exposed to the effects of all these interruptions in the year, divided by the total number of supplied recipients:

∑ Ni (2) = i SAIFI NT According to [7] SAIDI and SAIFI indices do not cover interruptions lasting less than three minutes. Automatic fault location, separation of faulty section, and recovery of supply for some recipients will substantially reduce SAIDI and SAIFI indices. Increased number of remotely controlled switches, along with faulted circuit indicators allows for separation of sections that supply smaller numbers of recipients, which in the case of failure occurring will result in a smaller number of recipients exposed to the effects of a long interruption.

Fig. 2. Example MV grid – e section isolation

Special Issue – Smart Grid

SAIDI index dependence on the number of remotely controlled points in a feeder. Below SAIDI index change estimates are presented, depending on the number of remotely controlled points in a feeder. The following simplifying assumptions have been adopted: • a feeder is considered divided into six sections with a normally open point switch in the middle of the feeder, • each section supplies the same number of recipients, • repair duration equals duration of the faulted feeder section’s location and isolation • location detection and repair duration is the same regardless of the faulted section • fault probability is the same in every section • “healthy” sections can always be supplied after isolation of the faulted section • in case of a single fault three feeder sections located between HV/MV substation and normally open point are not supplied. 1. SAIDI at no control and fault detection (before automation, n = 0, n – number of remotely controlled switches). Two sections remain not supplied for duration rl (duration of faulty section location and isolation), one section remains not supplied for duration rl + rn (duration of faulty section location and isolation plus repair)

r × N rl ×3 N r ×N + =4 SAIDI (n = 0 ) = n NT NT NT

(3)

where: r = rI = rn rn – duration of faulty section repair rl – duration of faulty section location and isolation

Comprehensive automation and monitoring of MV grids as the key element of improvement of energy supply reliability and continuity

N – number of recipients supplied from a single section NT – number of all recipients.

SAIDI (n = 4) = 0,5 ×

rn × N 8 + 0,5 × SAIDI ( n = 3) = SAIDI NT 24

× N section location 8 (7) 2. SAIDI for n = 1. Duration ofrnfaulty + 0,5 × SAIDI ( n = 3) = SAIDI (n = 0) SAIDI (n = 4) = 0,5 × and isolation shortens to 2/3 rN ,l Tone section may be 24 supplied after 1/3 rl. The repair duration remains unchanged. 6. SAIDI for n = 5. The faulty section location and isolation duration is less than 3 minutes (it’s not a long interruption). The repair duration remains unchanged: 2 1

SAIDI ( n =1) =

r ×2 N rl × N 8 r ×N 2 rn ×N 3 l + +3 = = SAIDI (n = 0) 3 NT 3 SAIDI ( n = 5) = rn × N = 1 SAIDI ( n =0) NT NT NT NT 4 (4)

1 ×2 N rl × N 8 r ×N 2 +3 = = SAIDI (n = 0) 3 NT 3 NT NT

3. SAIDI for n = 2. It is assumed that the fault occurrence probability on either side of the normally open point switch equals 0.5. For the side provided with an additional remotely controlled switch the faulty section location and isolation duration is shortened to 1/3 rl; one section may already be supplied after less than 3 minutes (it’s not a long interruption). The repair duration remains unchanged:

(8)

The above considerations apply only to the SAIDI index related to failures in MV grids. For the total SAIDI index faults in HV, MV, and LV grids are responsible:

SAIDI CALK = SAIDInn + SAIDISN + SAIDIWN

(9)

where: SAIDICALK – index for the whole company SAIDIWN – index portion, for which faults in HV grid are responsible SAIDISN – index portion, for which faults in MV grid are responsible 1 rl ×2 N SAIDI r ×N 3 13 nn – index portion, for which faults in LV grid are SAIDI (n = 2) = 0,5 ×( n + ) + 0,5 × SAIDI (n =1) =responsible. SAIDI (n = 0) NT NT 24 Based on analysis of the statistical data contained in (5) [1], it is ascertained that subject to simplifying assump1 rl ×2 N tion, SAIDIWN = 0 (no statistical data available to estimate ×N 3 13 + ) + 0,5 × SAIDI (n =1) = SAIDI (n = 0) the impact of faults in HV grids on the total index), the NT NT 24 share of SAIDInn and SAIDISN indices may be estimated in the total index based on the volume of electricity not 4. SAIDI for n = 3. Duration of faulty section location and supplied due to faults in LV and MV grids. Since the MV isolation is shortened to 1/3 rl; one section may already grid automation will not affect, or will insignificantly afbe supplied after less than 3 minutes (it’s not a long fect, the fault occurrence in LB grids, SAIDInn index may interruption). The repair duration remains unchanged: be expressed based on SAIDICALKO (index for n = 0 – i.e. before the automation):

1 r ×2 N rn × N 3 l 10 SAIDI ( n = 3) = + = SAIDI (n = 0) NT NT 24 (6)

5. SAIDI for n = 4. It is assumed that the fault occurrence probability on either side of the normally open point switch equals 0.5. For the side provided with an additional remotely controlled switch the faulty section location and isolation duration is less than 3 minutes (it’s not a long interruption). The repair duration remains unchanged:

SAIDInn = m × SAIDICALK0

(10)

where: m – coefficient calculated based on data from [1] – weight that determines the impact of LV grid faults on the ultimate value of SAIDICALK. In addition, the assumption is adopted that SAIDISN for the whole company will be close to the index calculated above for the hypothetical feeder – SAIDISN(n), while

SAIDISN (n) = wn ×(1 − m) × SAIDICALK0

(11)

where: wn = 1, 2/3, 13/24, 10/24, 8/24, 1/4 for n = 0, 1, 2, 3, 4, 5.

Special Issue – Smart Grid

Stanisław Kubacki, ENERGA-OPERATOR SA | Jacek Świderski, Institute of Power Engineering, Gdańsk Division Marcin Tarasiuk, Institute of Power Engineering, Gdańsk Division

SAIFI index dependence on the number of remotely controlled points in a feeder. SAIDICALK = SAIDICALK(n) = m × SAIDICALK0 + wn ×(1 − m) × SAIDI Below,CALK0 SAIFI index change estimates are presented depending on the number of remotely controlled × SAIDICALK0 + wn ×(1 − m) × SAIDICALK0 (12) points in a feeder. The same assumptions have been adopted as in the case of estimating the SAIDI inFor individual ENERGA-OPERATOR SA (EOP) divi- dex and the same reasoning has been repeated. It’s sions SAIDICALK index was calculated for n = 1, 2, 3, 4, been ascertained by analysing the statistical data 5, i.e. after the MV grid automation. In Tab. 1 the values contained in [1] that on their basis the weight of the of coefficient m are presented calculated for each EOP SAIFInn share in SAlFICALK cannot be accurately estidivisions. mated. Therefore coefficient m, calculated in the Fig. 3 shows the anticipated percentage change in course of determining the SAIDI index has been SAIDI index (in relation to SAIDI for n = 0) broken down adopted for the calculation. The following is obtained by EOP divisions, for various average numbers of remote- as a result of the estimates: ly controlled points in a single MV feeder. So finally

SAIFICALK (n) = m × SAIFICALK0 + kn ×(1 −m) × SAIFICALK0 (13)

where kn = 1, 1, 5/6, 2/3, 1/2, 1/3 for n = 0, 1, 2, 3, 4, 5. SAIFICALK index was calculated for n = 1, 2, 3, 4, 5, i.e. after the MV grid automation. Fig. 4 shows the anticipated percentage changes in SAIFI index (in relation to SAIFI for n = 0), broken down by EOP divisions for various average numbers of remotely controlled points in a single MV feeder. Fig. 3. Percentage change of SAIDI index depending on the number of remotely controlled switches in the MV feeder

The calculations show that SAIDI index is improved by increasing the number of controlled switches in the feeder. By deploying on average four controlled points in each feeder the index can be reduced by almost 50%. The index reduction varies from division to division because the shares in SAIDI of faults in LV, as estimated based on statistics [1], differ (from 12% in the Olsztyn division to 59% in the Toruńdivision). Where the impact of LV grid faults on SAIDI is higher, the possibility of reducing this index through actions in the MV grid is accordingly lower. Another conclusion from the analysis is that with the increase in the number of remotely controlled points in a feeder (four or more), the rate of SAIDI index improvement decreases (Fig. 3). This conclusion is confirmed by the analysis made by a Siemens AG team [2], whereby it’s been ascertained that a significant SAIDI reduction is achieved at about a 20% share of controlled points in the total number of points in a feeder.

Fig. 4. Percentage change of SAIFI index depending on the number of remotely controlled switches in the feeder

The calculations show that the SAIFI index is improved by increasing the number of remotely controlled switches in the feeder. By deploying on average three controlled points in each feeder the index may be reduced by approx. 20%. The index may be reduced by half in case five controlled points are employed in the

Tab. 1. Coefficients m for individual EOP divisions

Gdańsk

Elbląg

Kalisz

Koszalin

Olsztyn

Płock

Słupsk

Toruń

0.18

0.38

0.15

0.25

0.12

0.54

0.40

0.59

Special Issue – Smart Grid

Comprehensive automation and monitoring of MV grids as the key element of improvement of energy supply reliability and continuity

feeder. As with the SAIDI index, also SAIFI reduction varies from division to division depending on the share of LV grid faults in it, estimated based on statistics. Another conclusion from the analysis is that the rate of SAIFI index improvement is proportional to the number of remotely controlled points in the supply grid in the range of n = 1, …, 5 (Fig. 4).

5. SUMMARY The distance between DSO in Poland from companies in EU countries in terms of supply reliability, e.g. measured by the SAIDI index, is several fold. In Poland the SAIDI index is approx. 300 mins/ year, while in other EU countries to less than 60 mins/ year. In the coming years MV grid

automation can become one of the major challenges that distribution grid operators in Poland will face. The main driving factor will be the introduction by the regulator of financial incentives inducing the operators to improve the supply quality. All automated MV grid points should be covered by remote control, and provide the opportunity of fault indication and signalling. In some locations it is advisable to install more complex systems, including measurements of currents, power, and voltages. Additionally, a significant number of indoor substations (approx. 90% of all stations) should be equipped with faulted circuit indicators with remote monitoring from the dispatcher centre.

References 1. Report on the condition of G-10.5 electrical equipment for the year 2010 for ENERGA-OPERATOR SA. 2. Schroedel O. et al., Distribution Automation Solution – Impact on System Availability in Distribution Networks, 21. Conference Electricity Distribution CIRED, Paper No. 1117, Frankfurt, 6–9 June 2011. 3. Bachorek W. et. al., Dynamic Reconfiguration in MV Grids, V Conference: Electricity Losses in Power Grids, Kołobrzeg, June 2011. 4. Northcote-Green J., Kligsten J., Frohlich-Terpstra S., Transformation of Energy Networks: Initial Results from Intensified MV and LV Monitoring, 21. Conference Electricity Distribution CIRED, Paper No. 0792, Frankfurt, 6–9 June 2011. 5. Pulice M., Vidal E., Impact of Telesupervision in Substations MV/LV, 21. Conference Electricity Distribution CIRED, Paper No. 0524, Frankfurt, 6–9 June 2011. 6. Valtorta G., di Marino E., d’Orazio L., de Bianchi G., Corgiolu R., Misesti I., Functional Specification of DSO SCADA System to Monitor and Control Active Grids, 21. Conference Electricity Distribution CIRED, Paper No. 1159, Frankfurt, 6–9 June 2011. 7. Regulation of the Minister of Economy on 4 May 2007 on the detailed conditions for the power system operations as amended on August 21, 2008, Chapter 10, § 40.

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01/2012 number 10/year 4

Special Issue

The content of this publication is based on the results of work performed within the framework of the research stage entitled „Development of a conceptual design and a technical and business model for a medium-voltage smart grid in the context of cooperation between local energy sources under normal working conditions and in the event of network failure (possible island operation).” This stage is part of research task no. 4 entitled: „Development of integrated technologies for the production of fuel and energy from biomass, agricultural and other waste”, announced and supervised by the National Research and Development Centre and conducted by the consortium comprising: ENERGA SA – Robert Szewalski Institute of Fluid Flow Machinery of the Polish Academy of Sciences.

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