3-IJAEST-Vol-No.4-Issue-No.1-Rural-Home-Energy-Management-by-Fuzzy-Control-Model-for-Utility-Interfa by ISERP ISERP

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

Rural Home Energy Management by Fuzzy Control Model for Utility Interfaced Autonomous Solar(PV)-DG Power System in India S. N. Singh, Pooja Singh, Swati, Swati Kumari, R.Jha

Department of Electronics and Communication Engineering NIT, Jamshedpur (India) - 831014 Phone : +91-7739222532, +91-9852400837, +91-8083074877, +91-9431529577 , 91-9234597240 e-mail: snsnitjsr@gmail.com singhpooja219@gmail.com swati.verma200@gmail.com swati3458@gmail.com rishijha.jsr@gmail.com

emits poisonous health hazard gases like CO2, SO2 etc. Thus, need has been felt to look for a cost effective, more reliable autonomous sustainable renewable green power supply system which can be integrated with existing conventional grid system to meet the additional energy demand of these rural masses in order to provide the comfort in their life. An autonomous solar PV power supply system, with in-built battery back-up for rural home power supply integrated with distributed grid network as a supplementary source and its optimal utilization, has been proposed. PV plays a role of distributed primary energy source which meet almost all the base and critical load requirement of a rural house. A Grid supply is the supported/supplementary energy source to generate energy during peak load hours of a day and compensate the deficit of PV energy, stored in the battery, which arises due to varying insolation during low sun radiation period /cloudy weather day. A DG source as standby power source has been used to ensure continuous 7x24 hours supply in case of long failure of grid supply. Many authors have reported such systems in the past [1 2 3 ] but they lack in optimal design and its cost effectiveness has not been given due consideration in their systems. In the proposed scheme investigations have been carried out to study optimal sizing of system, operational measures in terms of its cost effectiveness and develop innovative technology for the same. This paper presents an approach for program realization on managing the power drawn from grid/DG network to its optimal value using soft computing fuzzy tool. The system is modeled to achieve the optimal control variables for getting the electricity at comparatively less economic price. . II. SOCIO - ECONOMIC PROFILE OF ADOPTED AREA OF CASE STUDIED

Abstract â&#x20AC;&#x201C; Electricity is the basic need of human living being. Its demand is increasing in almost all developing countries, including India, due to rapid growth of population. Conventional electrical supply systems are shrinking due to diminishing trend of its raw material. As a result, distribution of supply especially in rural sectors of our country has become almost standstill. An attempt has been made to integrate the present utility system with a cost effective supplementary source with renewable solar energy system to meet the additional demand of energy of rural houses. The system consists of power sources â&#x20AC;&#x201C; PV module 2x75Wp and distributed grid/DG (1.5kVA), different units such as bidirectional PWM inverter (300W) and energy storage device i.e battery (2x80Ah). A Fuzzy control intelligent system model for energy management has been developed to control power flow to be drawn mainly from PV energy, stored in 80Ah battery module, and optimizes the sharing of power from grid or DG. The system has been developed for maximum daily household load of 1800 with a demand factor of 0.9. This can be scaled to any value as per load power requirement ranging from 1200Wh/day to 3600Wh/day. The simulation study on a prototype module has resulted in an optimal yield leading to a cost effective system and saving of more than 50% power from conventional grid/DG source. Due to generation of green electricity by solar (PV) system, it has a very little impact of pollution on the life of villagers. The other features like self maintenance, portability, free fuel etc are the added advantages of the system. Keywords : Hybrid Power System; Photovoltaic; Distributed Grid; Fuzzy control; Diesel Generator etc.

INTRODUCTION

The demand of electricity is increasing day by day globally with the rapid growth of population. The additional demand of electricity cannot be met with the present system as the raw materials are diminishing and it has been anticipated that in the next 100 years all resources like coal, fuels etc will be exhausted completely. Presently DG sets integrated with grid supply are being used as an alternative source but due to high cost, rural masses can not afford this and use it in case of emergency supply only. More ever, it pollutes the environment also as it

ISSN: 2230-7818

Khairbony is a village located 10-15 km from main city in interior area in the district of East Singhbhum of Jharkhand State (India) having an approximate population of 1000, where main occupation is daily rated agriculture / industrial contractual labour. Although the village is having electric poles but

Page 15

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

electricity is distributed to rural houses with limited supply, controlled through circuit breaker with permissible current setting. Most of the villagers share electricity with grid or standby community owned 5kVA diesel fueled-engine generators or have their own individual LPG / diesel based unit with a rating of 550VA to run home appliances/lighting system or store energy in larger size of batteries for meeting entire energy need at user end. From the data acquired during survey, it has been revealed that in this area almost every home needs an average load energy ranging from 1.2kWh to 3.6 kWh/day.

The solar (PV)-grid/DG integrated home power supply system design comprises of the following module (Fig. 1(a)) : PV module Battery Bi-directional Power Converter(Inverter) Controller unit DG set as a supplementary standby power supply source etc.

The system is designed [4] for a rural home load requirement with the specifications as given below : Load Energy

PV size Battery Size

= =

1800 - 3600 Watt-hours over a period of 24 hour, with a demand factor of 0.9 and 50% sharing with grid power 4 X 75 Wp, 12 V 2x Dual 80Ah , 12 V low self discharge inverter grade tubular lead acid battery CFL lamps , Fans, TV and Rural Industrial /household equipment including pump etc 300W/750 VA, 12VDC ~ 220 V SPWM AC, 50Hz (distortion 5-15%)

    

(c) Figure1.(a) Block schematic of a solar power converter with a Standby DG Set (b) Power circuit Model (c) Prototype system module

III. SYSTEM CONFIGURATION AND OPERATION

(a)

(b)

ISSN: 2230-7818

Load(s)

Converter

Grid/DG set

Grid distributed network/Portable LPG 2X550VA/diesel based 1.5KVA

The primary source of power supply to rural houses is the PV power stored in the battery. Load power is managed either by PV system backed up by battery or supplementary integrated grid/DG source. The power converter unit of the PV system takes the low 12V DC voltage input from PV energy source, stored in battery bank, as shown in Fig. 1(b) and convert it into usable 220VAC, 50 Hz 300W/750VA output with the help of a transistorized centre tapped transformer (Tr) based push-pull configured BJT/MOSFET bi-directional converter (inverter) circuit (Fig. 1(c & d)). The controller circuit generates PWM square wave pulses, using IC CD 4047 based 50Hz oscillator, to activate and switch on IRF 540 MOSFET/ 2N3055 transistors T1 and T2 alternatively producing AC square voltage with low distortion at the output of secondary of transformer across the load. DG set is connected to load only when the stored PV energy falls below load energy and grid fails and battery reaches a discharge cut off level of 10.4V and remain on till battery attain a charge level to match with load energy requirement in the range of 12.8V to 13.4V. The intelligent, adaptive control action of the controller performs load power/energy management and thus monitor and manage to

Page 16

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

IV. FUZZY CONTROL SYSTEM MODEL

Fuzzy logic control has been used as an intelligent tool to integrate and manage energy sources to flow in the system in such a way that it meets the load power requirement in optimal way under varying condition. The system is comprised of PV module, a diesel generator, bi-directional inverter and energy storage battery device. The procedure in making the control designs are setting the constraints, assigning the linguistic variables and setting the rules for the controller. Solar radiations and load(s) are the areas that affect the studied outputs and hence load demand and the solar (PV) energy stored in battery are considered to be the input variables. The output variable of this controller is the duty cycle of operation i.e turn-on time (power sharing) period of the grid or generator at each sampling period of one hour depending on the battery charging status as decided by fuzzy control action. Input variable : Load and PV stored energy (%) Load (300 W)

Small Medium High

: : :

Trimf (0 20 40 ) Trimf (30 55 80 ) Trimf (70 85 100)

Small Medium High

: : :

Trimf (0 20 40 ) Trimf (30 55 80 ) Trimf ( 70 85 100)

The control strategy for an integrated power system is a control algorithm for the interaction among various system components. The system controller determines the switching on of grid supply or in case of grid failure, starting / stopping of the diesel generator, for feeding load power as well as charging battery operation. Determining the best condition of operation is the key to achieve optimal operation. Fig. 2 shows the power flow diagram of the system with input and output control parameters of control action. The inputs of the controller are the parameters such as unpredictable load power and renewable varying output solar energy stored in battery, whereas output parameter is the switching on/off grid /diesel generator. A power control strategy is also needed to control the flow of power and to maintain adequate reserves of energy during operational period continuously in the battery storage devices. The fuzzy based technique/algorithm [5, 6] has been implemented in the control strategy to achieve optimal minimal operation to draw power either from grid or DG resulting in saving on cost of electricity due to less fuel consumption .

V. FUZZY CONTROL ALGORITHM

deliver continuous power to load. The charging operation is performed either by PV source or grid/DG source through bidirectional converter circuit in its rectifying mode (comprising of diodes D1 and D2 while transistor T1 and T2 remain off). The intelligent controller prevents the battery to go into deep discharge/or overcharge as the case may be and thus battery never allows attaining a cutoff low voltage of 10.4V for deep discharging or 13.4V in case of overcharging. A proposed prototype PV power supply system module has been developed and installed at laboratory as per predicted load energy requirement of a typical rural house of the tribal village of Patamada block located in the outskirt remote area of Jamshedpur city (India).

Battery stored energy (10.4V - 13.4V )

Output variable : grid /DG operational time (%) Grid /DG::: System

Z : Grid/DG off (Low power sharing) P : Grid/DG on (HighPower sharing)

Trimf (0 25 50 )

Trimf(3065 100)

VI. SIMULATION OF FUZZY POWER CONTROLLER Knowledge based decisions, based on the input conditions of battery as well as load, have been formulated as a fuzzy rule and shown in Table (1). The output result i.e. P or Z activate the grid/DG to switch it ON or OFF respectively for a period evaluated as a crisp value using centroid method [7].

Figure 2 : A control strategy model of integrated PV-grid/DG integrated power system

ISSN: 2230-7818

Page 17

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

(A) Fuzzy rule output : The rule based outputs are represented as follows : 1.

If (L is S) and (B is S)

then O

If (L is S) and (B is M) If (L is S) and (B is H) If (L is M) and (B is S) If (L is M) and (B is M) If (L is M) and (B is H)

then O

then O then O

= =

then O then O

= =

then O

Z Z P Z Z P

then O then O

= =

3. 4. 5. 6. 7.

P Z

The load sensitivity analysis has been carried under varying energy storage status of battery. Energy flow takes place when battery stored energy remain more as compare to load demand otherwise power is shared with grid/DG for the time period as decided by fuzzy control action. The Energy balance equation is governed by the following equation (1) and (2) in two of its mode of operation : Mode I : PV energy stored in battery and feed power to load Load Energy (EL) = PV energy (EPV) stored in Battery EBAT (1) Mode II : Power drawn from Grid/or DG and feed power to load Load Energy (EL) = Grid Power (EEG)/DG Power(EDG)

The meanings of the labels designating the names of linguistic values are : L: load Energy, B : battery stored Energy, S: small, M: medium, H : high, O : DG, Z : Low power sharing, P : High power Sharing .

(B)Calculation for operational time in %. As a case study for typical demand of load power and energy stored in the battery status and the corresponding membership Function :

Load Energy (78%)  Medium (0.057) & High (0.533) Battery energy (32%)  Small (0.1) & Medium (0.32) Rules fired are 4, 5, 7 and 8

[ M(0.057)  [M(0.057)  [H(0.533)  [H(0.533) 

S(0.1)] M(0.32)] S(0.1)] M(0.32)]

= = = =

Strength of rule 4 : Strength of rule 5 : Strength of rule 7 : Strength of rule 8 :

0.057 0.057 0.1 0.32

(C ) Crisp Value :

An accurate method known as CENTROID Method has been used : =

= 60.73 %

ISSN: 2230-7818

(2)

The Fig. (3) reflects the output as % of ON period of grid/DG of its full value for one such set condition of Load Energy = 78% and Battery Energy status = 38%.(assume grid is unavailable and power is shared by DG).

8. 9.

If (L is H) and (B is S) If (L is H) and (B is M) If (L is H) and (B is H)

VI. RESULTS AND DISCUSSION

TABLE I. FUZZY RULE FOR CONTROL ACTION LOAD ENERGY Small Medium High BAT STORED ENERGY Small Z(1) P(4) P(7) Medium Z(2) Z(5) P(8) High Z(3) Z(6) Z(9)

Page 18

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

Fig. 4.: Rule viewer

Figure 5: . Surface viewer

VII. COST OF ELECTRICITY The PV system has been developed as a substitute for DG set being used in the past in conventional system. The cost analysis of electricity generation for PV system as well DG power system during its Life cycle period. The pay-back period comes out to be approximately 5-6 years when the cost of electricity reduces and become at par with the cost of electricity of grid (utility) supply.

Fig. 3 : Membership function of the fuzzy Controller (Top, Middle and Bottom)

ISSN: 2230-7818

Page 19

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

IX.

TABLE II. DAILY COST OF ELECTRICITY OF PV SYSTEM WITH DG SYSTEM PV Autonomous System /(Life Cycle in years)

Cost (Rs) Subsidised

Generator (1500VA)

PV Module (20 Years)

Rs 15000

Capital Cost (20 Years )

Rs 20000

Battery (3Years)

Rs 10000

Bank Loan Interest

Rs 150 Per Month

Bidirectional Converter (5Years)

Rs 5000

Fuel(Diesel)

Miscellaneous

Rs 100 PM

Miscellaneous

Cost of Electricity

Rs 15-20 Per day

Cost of Electricity

Solar (PV)-grid /DG integrated system has a great potential in future as one of the renewable energy technology which can meet the energy demands of grid deprived rural sectors. The hybrid technology, integrating PV with DG, offers solution to local power generation in terms of providing uninterrupted, reliable, qualitative (low distortion) and green supply without/with minimum use of standby DG at an effective cost. The easy installation and maintenance free operational feature of

Cost (Rs)

An attempt has been made to substitute DG set, being used by the rural masses in case of grid failure, by an integrated solar(PV)-grid/DG system towards sustainable power generation for rural electrification in the area especially in remote sectors where power availability from electrical grid network has become frequent due to limited generation of electricity. A design model of PV power supply system with battery back up for optimal control of grid/DG operation has been discussed. The simulated result show that introducing a fuzzy logic controller optimizes the power drawn from grid as well as running time of DG resulting in less consumption of fuel, thus reducing the cost of electricity and also prevent the environment to be polluted with hazardous gasses emitted from the DG system . The saving of DG fuel can go up to 30-100%.

Fig.6 : Payback period (Cost of Electricity)

Rs1500 Per Month Rs5000 Per Month Rs50-90 Per day

VIII. OPERATIONAL TIME : SHARING OF ENERGY SOURCES (PV ENERGY STORED IN BATTRY) GRID/ DG)

the PV power supply system has gained more popularity among the rural masses. The successful implementation of autonomous integrated PV- grid/DG system model has following outcomes : 



Average monthly PV energy (stored in Battery) shared with grid/DG in terms of operational time has been depicted in Table 5 during the year 2009.

TABLE III. PV ENERGY SHARED WITH GRID / DG ( %) IN TERMS OF OPERATIONAL SAMPLING TIME OF ONE HOUR (DURING 24 HOUR)

Jan’ 09

PV /Grid/DG energy OP Time shared (%) 40/50/10

July’09

PV/Grid /DG energy OP Time shared (%) 40/55//05

Feb

45/50/05

Aug

35/45/20

March

40/55/05

Sept

40/45/15

April

50/48 /02

Oct

45/40/15

May

50/48/02

Nov

50/35/15

June’09

40/58/02

Dec’ 09

40/45/15

Month

ISSN: 2230-7818

Month

CONCLUSION

Generating green electricity by PV module and meeting increasing load(s) demand of a rural house as well as preserving the nature. Cost effective with minimal hours of use of DG, thus consuming less fuel resulting in less maintenance as well as operational cost of electricity. REFERENCES

[1] [2] [3] [4] [5] [6] [7]

P. Lilienthal and E. Ian Baring-Gould, “Argentina: Rural Electrification Services”, National Renewable Energy Laboratory, 1999. King Mongkut’s University of Technology Thonburi, “Mini - Grid for Rural Electrification from Hybrid Systems”, 2002. M.R.Patel, “Wind and Solar Power Systems”, CRC Press, Boca Raton, Fl., 1999. S.N.Singh, A.K.Singh, “Optimal design of a cost effective solar home power system –an alternative solution to DG for grid deprived rural India” ,Vol 2, issue1(Jan 2010) T. Ross. Fuzzy Logic with Engineering Applications. University Science, 1989. Timothy J. Ross, “Fuzzy logic with engineering application”, Wiley India Pvt. Ltd. www.mathworks.com

Page 20

S. N. Singh et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 4, Issue No. 1, 015 - 021

Dr S.N. Singh had completed his M.Tech and doctoral Ph.D degree at the Department of Electrical Engineering, National Institute of Technology Jamshedpur (India) in 1991 and 2009respectively. He obtained B.Tech degree in Electronics and communication Engineering from BIT Mesra, Ranchi-Jharkhand (India)(A Deemed University) in 1979-80. Presently his area of interest is Solar Energy Conversion Technology. He had published more than 15 papers in National and International journals/conferences based on his. He had remained Head of Department of Electronics and Communication Engineering for two terms and presently heading Govt. of India sponsored VLSI (SMDP-II) Project.

Swati had published three papers in National as well as in International journal. She is pursuing B.Tech. course in the Department of Electronics & Communication Engineering in National Institute of Technology (An Autonomous Institution under MHRD, Govt. of India) Jamshedpur (India) and a active member of VLSI Project (SMDP-II) scheme sponsored by Ministry of Information Technology, Government of India.

Rishi Kumar Jha is pursuing his M. Tech in VLSI Design and Embedded System in the Department of Electronics & Communication Engineering in National Institute of Technology(An Autonomous Institution under MHRD, Govt. of India), Jamshedpur( India). He has been an educational consultant for the past 15 years.

BIOGRAPHIES

Pooja Singh had published two papers in National and one paper in International journal. She is a pursuing B.Tech. course in Electronics in the Department of Electronics & Communication Engineering in National Institute of Technology (An Autonomous Institution under MHRD, Govt. of India) Jamshedpur (India) and a member of VLSI Project (SMDP-II) sponsored by Ministry of Information Technology, Government of India.

Swati Kumari had published two papers in National and one paper in International journal. She is pursuing B.Tech. course in the Department of Electronics & Communication Engineering in National Institute of Technology (An Autonomous Institution under MHRD, Govt. of India) Jamshedpur (India) and a member of VLSI Project (SMDP-II) sponsored by Ministry of Information Technology, Government of India.

ISSN: 2230-7818

Page 21