I

OPTIMAL DESIGN OF A MINI-GRID FOR SUSTAINABLE INTEGRATED COASTAL DEVELOPMENT USING

GENETIC ALGORITHMS

A THESIS

BY

SAIFUL AZAM SIDDIQUE Examination Roll No. 06 Ag. Engg. FPM-JD 01M

Reg. No. 28474 Session: 2000-2001

Semester: January-June, 2008

MASTER OF SCIENCE (M.S.) IN

FARM POWER AND MACHINERY (AGRICULTURAL ENGINEERING)

DEPARTMENT OF FARM POWER AND MACHINERY BANGLADESH AGRICULTURAL UNIVERSITY

MYMENSINGH-2202

May 2008

II

OPTIMAL DESIGN OF A MINI-GRID FOR SUSTAINABLE INTEGRATED COASTAL DEVELOPMENT USING

GENETIC ALGORITHMS

A Thesis

By

SAIFUL AZAM SIDDIQUE Examination Roll No. 06 Ag. Engg. FPM-JD 01M

Reg. No. 28474 Session: 2000-2001

Semester: January-June, 2008

Submitted to the Department of Farm Power and Machinery

Faculty of Agricultural Engineering and Technology Bangladesh Agricultural University, Mymensingh

In partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE (M.S) IN

FARM POWER AND MACHINERY (AGRICULTURAL ENGINEERING)

DEP ARTMENT OF FARM POWER AND MACHINERY

BANGLADESH AGRICULTURAL UNIVERSITY MYMENSINGH-2202

May 2008

III

OPTIMAL DESIGN OF A MINI-GRID FOR SUSTAINABLE INTEGRATED COASTAL DEVELOPMENT USING

GENETIC ALGORITHMS

A Thesis

By

SAIFUL AZAM SIDDIQUE Examination Roll No. 06 Ag. Engg. FPM-JD 01M

Reg. No. 28474 Session: 2000-2001

Semester: January-June, 2008

Approved as to style and content by:

(Professor Dr. B. K. Bala) Supervisor

(Professor Dr. Md. Ashraful Haque) Co-supervisor

(Professor Dr. Ashraful Haque) Chairman

Examination Committee and

Head Department of Farm Power and Machinery

Bangladesh Agricultural University Mymensingh

May 2008

IV

ABSTRACT

Power grid cannot reach everywhere. Yet there are alternatives. Renewable

energy can offer an ideal source of electricity for the communities far from a

grid- on an island, or other isolated situations. Such alternatives are hybrid

photovoltaic systems.

This research presents an optimal design of a solar-diesel hybrid mini-grid

system for 132 families in an isolated island-Sandwip in Bangladesh. The

electrical load is considered based on the local needs and the electrical load

demand is 20 kWh. The system is optimized using genetic algorithms. If the

renewable energy source produces more than the one required by the loads,

they excess energy can be used to charge the battery while if the amount of

energy demand is higher than the one produced by the renewable energy

source, the control strategy determines the most economical way to meet the

energy deficit.

V

ACKNOWLEDGEMENT

First and foremost I would like to express my deepest sense of gratitude to the lord

of the universe “Almighty Allah" and His holy prophet Hazrat Mohammad (SM)

who have been constantly guiding throughout troubled journey of my life. Without

the help and shepherding love of “Almighty Allah” nothing is possible, let alone this

simple research work.

I warmly recognize my continuing heartiest gratitude, sincere appreciation and

profound regards to my revered teacher and research supervisor Professor

Dr. B. K. Bala, Department of Farm power and Machinery, Bangladesh

Agricultural University, Mymensingh who in spite of his busy schedule in time and

abroad, always had time to spare for creative suggestions, constructive criticism,

helpful comments and encouragement all the time. His unparalleled magnanimity,

immense guidance, constant encouragement and constructive advice are also deeply

appreciated.

I also like to express my grateful appreciation and deep sense of respect to my co-

supervisor Professor Dr. Md. Ashraful Haque, Head, Department of Farm power

and Machinery, Bangladesh Agricultural University, Mymensingh for providing

necessary facilities and helpful suggestions during the course of research work.

I would like to take this opportunity to express grateful appreciation indebtedness

to all respected teachers in the Department of farm Power and Machinery,

VI

Bangladesh Agricultural University, Mymensingh for their help extended in this

research.

Special thanks are due to the staff of REB, Dhaka, for extending all possible helps

in related information. Special thanks to General Manager of Sylhet PBS-2 to let

me free for data collection.

Last but not the least, I profoundly acknowledge gratitude of Md. Ashik-E-

Rabbani, Assistant Professor Department of Farm power and Machinery,

Bangladesh Agricultural University, Mymensingh who helped me very much, and

other well-wishers who helped in many ways and sacrificed a lot during completion

of the research work.

The author

VII

CHAPTER

CONTENTS

TITLE PAGE NO.

ABSTRACT iv

ACKNOWLEDGEMENT v

LIST OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES x

GLOSSARY xiii

CHAPTER 1 INTRODUCTION 1

1.1 Introduction 1

1.2 Positive impact of solar-diesel hybrid system

4

1.3 Objectives 6

CHAPTER 2 REVIEW OF LITERATURE 7

CHAPTER 3 SOLAR PHOTOVOLTAIC SYSTEM 20

3.1 Introduction 20

3.2 Systems 21

3.2.1 Stand-alone systems 23

3.2.2 Grid linked systems 24

VIII

CHAPTER

CONTENTS (Contd.)

TITLE PAGE NO.

3.3 The Solar Cell 26

3.3.1 Doping 27

3.3.2 The p-n junction 28

3.3.3 The volt-ampere characteristics 31

3.3.4 Generation of electron-hole pair by photon absorption 33

3.4 Technical Aspects of Solar Cells 34

3.4.1 I-V characteristic of solar cells 34

3.4.2 Short- circuit current and open-circuit voltage 35

3.5 Effect of irradiation 36

3.6 Effect of Fill Factor 37

3.7 Effect of Temperature 37

3.8 Radiation Absorption and Material Selection 38

3.9 Maximizing of Solar Cell Performance 40

3.10 The PV Module and Array 40

3.11 Energy Storage 42

3.12 Associate Electronic Components 43

3.12.1 Charge controller 43

3.12.2 Inverter 43

3.13 Balance of System Components 44

IX

CHAPTER

CONTENTS (Contd.)

TITLE PAGE NO.

CHAPTER 4 Methodology 45

4.1 Optimal Design Using Genetic Algorithm 45

4.1.1 Cycle charging strategy 48

4.1.2 Combined strategy 48

4.2 Develop genetic algorithm 49

4.2.1 Main algorithm 50

4.2.2 Secondary algorithm 51

4.2.3 Implementation of the GA 52

4.3 Case study: Sandwip-an Isolated Island 55

4.3.1 Characteristics of the island-Sandwip 55

4.3.2 Energy requirements in the community 58

4.4 Design Layout 59

CHAPTER 5 RESULT AND DISCUSSION 60

5.1 The optimized system configurations 60

5.2 The control strategies 61

CHAPTER 6 CONCLUSION 65

REFERENCES 66

X

LIST OF TABLES TABLE

TITLE PAGE NO

3.1 Properties of lead acid storage battery 43

3.2 Summary of inverter performance 44

LIST OF FIGURES

FIGURE PAGE NO

1.1 Growing energy demand of the World 1

3.1 Schematic diagram of a photovoltaic system 21

3.2(a) System operation during day time 22

3.2(b) System operation during night time 22

3.2(c) System operation during shortfall 22

3.3 PV system directly connected to load 23

3.4 Basic stand–alone PV system 23

3.5 Hybrid stand-alone PV system 24

3.6 Grid back-up PV system 25

XI

FIGURE LIST OF FIGURES (Contd.)

PAGE NO

3.7 Grid connected PV system 26

3.8 Illustration of the effects of doping 27

3.9 Schematic diagram of p-n junction including the charge density and electric intensity

29

3.10 Volt- ampere characteristics of an ideal p-n diode 32

3.11 Volt- ampere characteristic of an ideal p-n diode with expanded scale for reverse current

33

3.12 Illuminated I-V characteristics 35

3.13 I-V characteristics of solar cell under different illumination levels 37

3.14 Temperature dependence of PV curve of a solar cell 38

3.15 Variation of ∞ with photon energy for different semiconductors 39

3.16 Photovoltaic module 41

4.1 Flowchart of HOGA 54

4.2 The location map of Sandwip, Bangladesh 56

4.3 Monthly average daily load profile 58

4.4 Average daily solar radiations 59

4.5 Schematic diagram of batteries in series and parallel connection 59

5.1 Total net present cost and emissions a function of the main

Algorithm generations. 62

5.2 Power generation capacity of the PV generator, AC generator and

inverter

63

XII

FIGURE LIST OF FIGURES (Contd.)

PAGE NO

5.3 Annual energy balances the hybrid system 64

5.4 Cost of the different elements of the hybrid system as percentage of

the total net present cost 64

List of Appendix

TABLE

TITLE PAGE NO

A.1 PV modules specifications and costs 78

B.1 Batteries specifications and costs 78

C.1 Inverter specifications and costs 79

D.1 Generator specifications and costs 79

E.1 Monthly Average daily solar insolation Horizontal Surface 80

XIII

1.1 Introduction:

CHAPTER 1 INTRODUCTION

In most of the developing countries, the portions of the population living in the

remote and isolated locations do not have access to the electrical grid line. Yet

there are alternatives. Renewable energy can offer an ideal source of electricity

for an island or other isolated places far from national grid.

Figure 1.1 shows the growing demand of energy for the world (Sarma, 2002).

The dreadful scarcity of energy has made the nation conscious to harness new

renewable sources and to take measure of conservation. Besides, electricity

generation from conventional sources (natural gas, oil, etc.) releases incredible

amount of pollutants (CO2, SO=2, Nitrogen-oxide, etc.). To combat this

adverse situation, alternative and environment-friendly energy sources are

being considered highly. In this respect, solar-hybrid mini-grid technology

stands out to be one of the prospective candidates. The world’s petroleum

production increases exponentially and will reach tits peak in nearly 2010 and

after that it will decrease (Sarma, 2002).

Fig. 1. Growing energy demand of the world

0

100

200

300

400

500

600

700

800

900

1972 1985 2000 2020

Year

Ene

rgy

dem

and

(hex

jule

s)

Fig. 1.1

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In some cases, there is very small local electric power generating plants

running mostly by diesel sets and mainly to give supply to government offices

and to some public consumers. It may be mentioned that the potential demands

of electricity are very much higher compared to the actual demand, which are

higher, compared to the demand which are currently being served with such

limited generation. Diesel sets operate very inefficiently at less than full

capacity, so sometimes the addition of some storage can save not only on

capacity but also on fuel and operating expenses. In some remote areas and

isolated coastal locations solar energy may also be utilized to save fuel costs.

However, to achieve long life and optimal performance from hybrid system of

diesel, wind and solar energy particularly those supplemented with battery

storage required that their operation be carefully controlled. For the consumer

contemplating the installation of such a system the major concerns may be the

suitable sizes for each component to satisfy a given load profile and the

costing of alternate systems in a consistent framework.

Solar energy is one of the inexhaustible, free, abundant, site-dependent, non-

polluting and potential sources of renewable energy options, which is being

pursued by a number of countries with monthly average daily solar radiation

level in the range of 3-6 kWh/m2, in an effort to reduce their dependence on

fossil-based non-renewable fuels (Post and Thomas, 1999). Solar collectors

can be classified as either solar to thermal energy converters or solar to electric

energy converters. Devices that directly convert solar/light into electricity are

called photovoltaic. Moreover, concept of PV is well conceived and presently

(in spite of market barriers/impediments) thousands of PV systems are being

installed worldwide, for providing power to small, remote, grid-independent or

XV

stand-alone applications (Post and Thomas, 1999). Annual worldwide

shipments of PV panels have grown from 2 MWp in 1975 to 135 MWp in

1998. World PV market grew by 26% in 2002 when compared with 2001 in

the year 2003. During last coupled of years, substantial progress has been

made in key area such as quality, reliability (20+ year warranties) and

efficiency of solar panels. The price of PV modules has dropped by a factor of

1/30 during the past 20 years. Germany, Japan and the Netherlands are leading

the solar race notably (Greenpeace briefing). Typical ratings of PV modules

vary from 30 to 300 Wp.

A hybrid technology is a combination of multiple sources of energy; such

renewable energy and diesel generator and may also include energy storage

such as battery. Mini-grid power generation is meant to supply remote areas

where grid connection is almost impossible in terms of cost and geography,

such as islands, aborigine’s villages and areas where conservation of nature is

a concern. For these, we intend to design a solar-diesel hybrid system based on

the local needs.

The design and operation control is not a linear problem due to non-linear

component characteristics with a large number of variables. The optimal

design of problems like this cannot be achieved easily using classical

optimization methods. This study presents a method of optimization for PV-

Diesel systems using a Genetic Algorithm (GA) (Dufo-Lopez, R et al., 2005).

Genetic Algorithms are an adequate search technique for solving complex

problems when other techniques are not able to obtain an acceptable solution.

The PV-hybrid system studied is an AC-only system.

XVI

There are some programs that simulate hybrid systems, such as HYBRID2

developed by the NREL (National Renewable Energy Laboratory, USA) and

TRNSYS developed by the university of Wisconsin (USA). HYBRID2

simulates hybrid systems with very high precision calculations, but it does not

optimize the system. TRNSYS was initially developed to simulate thermal

systems but it has incorporated PV systems to simulate hybrid systems such as

those proposed here, however it cannot optimize them.

HOGA, the program used in this study optimizes the hybrid PV-Diesel system

using Genetic Algorithms (Dufo-Lopez, R et al., 2005). The program

calculates the optimal configuration of the system. This optimal configuration

is described very precisely: the number of PV panels and the type of battery,

the inverter power, the diesel generator power, the optimal control strategy of

the system with its parameters, the Total Net Present Value of the system and

the different relative costs such as the fuel cost, and finally, the number of

running hours for the diesel generator per year. The program also optimizes

the dispatch strategy, as does HOMER, but it also optimizes the SOC set point,

that is an important variable.

1.2 Positive impact of solar-diesel hybrid system

A robust power supply and downtime minimization during power outages

could be achieved by virtue of varying the power sources, which is vital indeed

due to its ability to provide backup power. System failure or disruption of

diesel supply to the community is the factor leading to utilize an alternate

generating system encompassing renewable energy/diesel hybrid system as to

encourage continuous and in power supply. Photovoltaic and wind energy

XVII

systems are attributive to fewer moving parts, repairs or routine maintenance.

In fact, renewable energy sources being indigenous and free, is more securing

than diesel thus, beneficial to facilities.

Improved energy services

The ability of renewable energy working in tandem with diesel, contributes to

high quality and dynamic electricity services for 24 hours/day whilst in a

conventional system, the high diesel operating costs limits the power supply

only to 12 hours/day. The cost of photovoltaic or wind power generation lies in

the form of upfront capital expenditures whereby the operation and

maintenance expenses are low. Therefore, the generating cost via photovoltaic

or wind is marginally more than a conventional system with respect to the

additional generating capacity promising a satisfaction of a continuous supply

of electricity supply to the customer.

Reduced emission and noise pollution

Diesel generation emits air and water pollution agents as well as loud noise,

proving the essentiality of renewable energy or diesel retrofits application in

generating power, which adopts an environment-friendly technology. In fact,

renewable energy system is also substantially better than diesel generators.

Continuous power

By incorporating diesel generator with renewable energy system, diesel

generator is able to boost up the electricity supply during sudden increase in

energy demand or when the batteries capacity decreases and thus, facilities

face no interruption of supply.

Increased operational life

XVIII

The alternate operation at regular intervals and specific occurrences of

renewable energy and diesel hybrids could prolong the life of the overall

system on account of the discontinuous usage of the diesel set. Furthermore,

the discharging level of the batteries is optimum, contributing to its increased

operational life.

Reduced cost

Hybrid system promotes efficient use of power since renewable energy system

could be configured to cope with base load whilst the peak load could be met

through diesel generator.

1.3 Objectives

The main objective of this study is optimal designing of mini-grid using

Genetic Algorithms (GA).The specific objectives are:

i) Optimization of PV-diesel hybrid systems for mini-grid using

Genetic Algorithm (GA)

ii) Optimization of operational control strategies

XIX

REVIEW OF LITERATURE

Chapter 2

Yang et al. (2007) developed the hybrid Solar-Wind System Optimization

Sizing (HSWSO) model, to optimize the capacity sizes of different

components of hybrid solar-wind power generation systems employing a

battery bank. With the incorporated HSWSO model, the sizing optimization

of hybrid solar-wind power generation systems can be achieved technically

and economically according to the system reliability requirements. A case

study is reported to show the importance of the HSWSO model for sizing the

capacities of wind turbines, PV panel and battery banks of a hybrid solar-wind

renewable energy system.

Ashok (2006) reported that Hybrid energy system is an excellent solution for

electrification of remote rural areas where the grid extension is difficult and

not economical. Such system incorporates a combination of one or several

renewable energy sources such as solar photovoltaic, wind energy, micro-

hydro and may be conventional generators for backup. This paper discusses

different system components of hybrid energy system and develops a general

model to find an optimal combination of energy components for a typical rural

community minimizing the life cycle cost. The optimal operation shows a unit

cost of Rs. 6.5/kWh with the selected hybrid energy system with 100%

renewable energy contribution eliminating the need for conventional diesel

generator.

XX

Dufo-Lopez, R et al. (2006) reported a strategy, optimized by genetic

algorithm, to control stand-alone hybrid renewable electrical systems with

hydrogen storage. The strategy optimizes the control of the hybrid system

minimizing the total cost throughout its lifetime. The optimized hybrid system

can be composed of renewable sources (wind, PV and hydro) batteries, fuel

cell, AC generator, and electrolyzer. If the renewable sources produce more

energy that the one required by load, the spare energy can be used either to

charge the batteries or to produce H² in the electrolyzer. The control strategy

optimizes how the spare energy is used. If the amount of energy demanded by

the loads is higher than the one produced by the renewable energy sources, the

control strategy determines the economical way to meet the energy deficit. The

optimization of the various system control parameters is done using genetic

algorithms.

Koutroulis et al. (2006) presented a methodology for optimal sizing of stand-

alone PV/WG systems. The purpose of the proposed methodology is to

suggest, among a list of commercially available system devices, the optimal

number and type of units ensuring that the 20-year round total system cost is

minimized subject to the constraint that the load energy requirements are

completely covered, resulting in zero load rejection. The 20-year round total

system cost is equal to the sum of the respective component’s capital and

maintenance costs. The cost (objective) function minimization is implemented

using genetic algorithm, which, compared to conventional optimization

methods such as dynamic programming and gradient technology have the

ability to attain the global optimum with relative computational simplicity. The

XXI

proposed method has been applied for the design of a power generation

system, which supplied a residential household.

Agustin et al. (2005) reported the Strength Pareto Evolutionary Algorithm to

the multi-Objective design of isolated hybrid systems. The design is posed as

an optimization problem whose solution allows obtaining the configuration of

the system as well as control strategy that simultaneously minimizes both the

total cost through the useful life of the installation and the pollutant emissions.

Dufo-Lopez, R et al. (2005) reported Hybrid photovoltaic systems (PV-hybrid)

use photovoltaic energy combined with other sources of energy, like wind or

diesel. If these hybrid systems are optimally designed, they can be more cost

effective and reliable than PV-only systems. However the design of hybrid

systems is complex because of the uncertain renewable energy supplies, load

demands and the non-linear characteristics of some components, so the design

problem cannot be solved easily by classical optimization methods. When

these methods are not capable of solving the problem satisfactorily, the use of

heuristic techniques, such as the genetic algorithm, can give better results.

Bala et al. (2007) reported that renewable energy can offer an ideal source of

electricity for the communities far from a grid on an island, or other isolated

situation and also presented design and economics of a solar-diesel hybrid

mini-grid system for 132 families in an isolated island-sandwip. The electrical

load based on the local needs and electrical load demand is 20 kWh. The

sizing of the hybrid system consists of 31 solar modules, 10 number of 24 V

batteries, 2 Inverters having a total capacity of 24 kW, 24 V DC/220 V AC. A

XXII

diesel generator set of 12 kW capacities is selected for backup during shortfall.

The life cycle cost (LCC) is estimated and LCC is found to be Tk.15.51 per

kWh compared to electricity price of Tk.4.00 per kWh.

Hontoria et al. (2004) developed several methods for sizing stand- alone

photovoltaic (PV) systems. The more simplistic were called intuitive methods.

Those were useful tool for a first approach in sizing stand-alone photovoltaic

systems. Nevertheless they were very inaccurate. Analytical methods also used

to describe the PV systems size as a function of reliability. These ones are

more accurate than the previous ones but they are also not accurate enough for

sizing of high reliability. In a third group there are methods, which use system

simulations. These ones are called numerical methods. Many of the analytical

methods employ the concept of reliability of the system or the complementary

term: loss of load probability (LOLP). An improvement for obtaining LOLP

curves based on the neural network called Multiplayer perception (MLP) is

also described.

Ismail et al. (2003) reported a pilot project on solar hybrid power system. The

objective of this project was to design and install the solar power station at

remote location and to develop a standard design of stand-alone solar power

station suitable for Malaysia. The main domestic energy is for residential

purpose (e.g. small lighting unit, radio, b/w television, small fans, charger

etc.). The load demand was calculated based on the diesel generator set. The

generator capacity is 18.6 kW. The design of solar panel was done both for the

home and small application at ‘Kampung Denai’. The maximum demand was

4195.35 kW. The plot centralized solar power station consists of 10 kW

XXIII

inverter, 150 kWh batteries and other balance of systems. The status of the

system, operational and maintenance issues, load profile of the solar power

station and economics and system designs of the whole system are also

presented.

Sopian et al. (2003) studied a photovoltaic (PV) system to provide the

electricity for a single residential household. It was found that providing

electricity for a household by using PV system would be beneficial and

competitive for long-term investment, especially in case of reduction of the

price of the system as well as efficiency.

Malayappan et al. (2003) design a decentralized hybrid energy system using

solar, wind and biomass gasifier coupled with diesel generator for a particular

village. The energy requirement of electrical lamps, fans, TV, radio and home

appliance equipments in database to calculate the demand for the village. The

solar radiation data, wind energy data, availability of carbonaceous waste

materials of that particular village and the demand are given as input data for

the program .The proposed program will calculate the amount of energy that

can be extracted from the sources, number and size of solar panels, size and

capacity of wind generator and size of gasifier. The wind sweep and solar

panel area are optimized based on the cost of energy generation (wind @ Rs.

2.75 per unit and solar @ Rs 2.60 per unit) by using LPP graphical method.

From the obtained wind sweep area (17.4085 m²), the diameter of the windmill

is calculated to be 4.71 m

Rahman (2003) reported the renewable energy technology for off-grid power

generation using solar-hybrid system. The hybrid technology offered a solution

XXIV

to off-grid power generation in terms of reducing operation, cost, maintenance

and logistic problems providing 24-hrs reliable supply at an effective cost as

well as preserving the nature.

Colles et al. (2003) reported an analytical approach to evaluate and to optimize

the life cycle saving of hybrid diesel-photovoltaic plants. The life cycle

savings is evaluated, considering one or more diesel generator sets, operating

in different fixed power levels, with special attention to the case of high

specific fuel cost. The condition under which optimum photovoltaic module

area exists is analyzed. In the particular region of the northern part of Brazil, it

is shown that there were several favorable conditions to implement

photovoltaic generation, in the range of current electricity tariffs and diesel oil

costs practiced in market.

Sarma and Mahapatra (2002) reported that the choice between off-grid solar

photovoltaic power generation and conventional option of extending the

national grid of remote village electrification. The initial capital investment of

photovoltaic (PV) system is very large but this study shows that for the

villages having low-load demand and being remote decentralized power

supply by PV system can be cost competitive in terms of life cycle cost of unit

energy (LCC). Costs and distances from the load centre to the exiting grid line

are high though the per unit electricity generation cost of conventional

centralized power generation is low. The LCC of grid extension is dominated

by the grid extension cost and the generation cost has little impact on it,

whereas LCC of PV system is dominated by the cost of arrays and battery

replacement cost. The life cycle cost of PV (Rs./kWh) varies from Rs.17.62 to

XXV

Rs. 17.45 for the load variation of 7.5 kW to 50 kW. The optimal economic

distance (OED) for having a PV system for different loads; for low load profile

the PV is more cost effective than the conventional extension of grid and vice

versa.

Bhuiyan and Asgar (2002) studied the performance of the SAPV system and

found to be satisfactory and the experimental results coincide well with the

theoretical estimates. The charging time of the battery is found to decrease by

about 2% when the azimuth angle of the array is changed from 00 to ± 450

facing south, thus increasing the output power for the PV modules.

Vandenbergh et al. (2003) presented the operational experience of mini-grids

of two pilot plants based on the AC coupled PV technology. The first plant

was the ‘Starkenburger Hùtte’ a single user system in the Austrian Alps and

the performance ratio of the PV field could be improved by adding new battery

capacity. The second system was a multi-user micro-grid located in a remote

area on the Greek Island of Kythnos. Both systems were operated with

satisfactory performance.

Sasithranuwat and Rakvichian (2003) added the concept of single-user mini-

grid applied to design the electrical power system for isolated offices located

in remote areas that have no access to electricity. This electric power system

was referred as Photovoltaic for Isolated Office System (PIOS). The operating

principle of the system is to use the solar radiation during daytime to supply to

the load directly via the photovoltaic panels and at the same time, storing the

excess energy in the battery bank for continued electricity supply at night. The

system made use of two different inverters to perform the above tasks. The

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first inverter, known as a grid inverter, converts DC from the PV array to AC

and supplies directly to the load during the daytime, while the second inverter,

also known as a battery inverter, is used to convert DC from the battery to

supply to the AC at night. In case of insufficient solar radiation, a built-in load

management control module will be used to ensure the stability and reliability

of the system. From the simulated results by using the Res. 2.0 simulation

software, it was found that the yearly average solar fraction was 87.3%; the

performance ratio was 33.3% hr/day.

Zahedi (2003) reported an accurate sizing of components in the PV hybrid

power systems. Accurate sizing, which avoids wasting electricity and money,

is an important part of the design of PV hybrid systems. Another issue was to

show the results of this sizing method for a system which supplies electricity

for facilitated lighting at the site located at the latitude of 370-32' south and

longitude 1430-49' east. Normally the generator will charge the batteries from

about 20% to about 70%. Charging the batteries from 20% to 70% in five

hours requires a charging rate of c/10. Size of components required to supply

electricity for a load which needs 18 kWh per day, efficiency of the

components:-inverter: 95%; battery efficiency: 85% with depth of discharge of

80%, wiring efficiency: 98%, size of the inverter: 3.5 kW, 48 DC to 240 AC, 2

diesel generators, 4 kW each to support the battery bank. Volume of fuel

required in one year: 3200 litre, total electricity required by load in one year:

6570 kWh, % of load covered by solar PV by solar PV array: 65% considering

number of consecutive no sun. 5 days and finally presented the performance

predication of the PV hybrid system was presented.

XXVII

Sarkar and Obaidullah (1999) conducted a performance study on the prospects

of solar photovoltaic for vast application in the far-flang rural areas of

Bangladesh. The performance and economic analysis of a stand-alone solar PV

system in Bangladesh was analyzed. The system was designed and installed to

supply electricity to 14 fluorescent lamps in a laboratory of BUET. The system

consists of PV modules, charge control unit, batteries, switching circuits, and

connecting wires. The total load is estimated for four hours of operational day.

The performance data presented the proper choice of system components and

proper installation, the PV system operated properly. The life cycle cost (LCC)

of the PV system had been compared to the diesel generator. From the

economic analysis of the system it was found that the life cycle cost of the PV

system lesser than that of diesel generator.

Jurge and Huacuz (2001) attempted to test new schemes that could help to

solve the problem of electrifying remote rural communities. The Mexican

Government launched an initiative in 1989 to use locally available renewable

energy sources to do the job. Since then, small hydroelectric power plants,

wind generators, photovoltaics and hybrids thereof have been installed in

growing numbers. Over 1700 small rural communities had been electrified

using solar home systems, amounting to almost 50,000 photovoltaic

installations consisting of one or two PV modules, one lead-acid battery and

one electronic charge controller. Users can also use three or four compact

fluorescent lamps, radio and small B & W television for entertainment where

TV signals are available. Communal services such as medical dispensaries,

schools, meeting halls and churches have also been PV powered by the

XXVIII

hundreds, while over 12,000 rural telephones powered by photovoltaics had

been installed in Mexico.

Sarkar and Obaidullah (1999) designed a stand-alone PV home lighting system

for 4 hours daily operation. The PV array was selected to operate on average

weather conditions of solar radiation. The array sizes were designed to operate

even in the month of minimum insolation considering different types of power

losses. Three panels (3 × 60 Wp) charge five lead-acid batteries and it supplies

electricity to twelve fluorescent tube lights of each 8-watt capacity.

Post and Thomas (1999) examined photovoltaic power system applications,

including remote SPV, dispersed grid-connection and large generation centers.

Photovoltaic system options for both current and future application are

described and costs for each of these options are determined. The computed

results show that the future applications will utilize the renewable energy

technology available today.

Huq (1999) reported the implementation of Narsingdi SPV project, which was

under supervision, and partial finance of the Govt. of Bangladesh with a major

finance of French Govt. The main objective of the project was to test the

financial and economic viability, technical acceptability, social demand,

acceptance and popularity of SPV systems by the rural population. Selection of

project area was on the basis of non-electrified, remote rural communities, far-

flung islands.

Bhuiya et al. (1999) designed a stand-alone photovoltaic power system to

operate residential appliances such as fluorescent lamp incandescent light

XXIX

using standard methods. The total load is estimated for four hours of operation

per day. The battery is sized considering different factors that affect battery

efficiency to reliably operate the estimated loads during a sequence of below

average isolation. The minimum battery size is obtained to be 128 Ah @ 100

hr, 24 V. The PV array is sized to operate the load on a daily basis based on

average weather conditions using monthly average daily values of solar

radiation data for eleven years. The array is sized to proper sizes in order to

operate the estimated loads reliably in the month of minimum insolation taking

into account different types of power losses. The minimum array size was

obtained as 6 × 47 Wp.

Vosseler et al. (1999) applied the integrated approach for high standard energy

services by Multi-user PV Hybrid Grids. An integrated socio-technical

methodology was developed which reduces costs due to optimized sizing and

reduction of failures due to inadequate user behaviour. The methodology

“Energy Dispenser/Meter” (patented) gave a solution to the energy distribution

in the rural community of Spain.

Murali et al. (1999) designed a solar-wind hybrid system. In choosing the

contribution of renewable energy sources, the storage demand and its

associated decrease in energy price were taken into consideration. The costs of

battery bank account for the critical components in the overall project cost.

The hybrid power plants can work with small battery banks. Moreover solar

and wind energy complement each other in that wind is available whole the

day-night in areas with good regime. For reliability and efficiency, a

Permanent Magnetized Generator (PMG) of 1.5 kW nominal output is chosen.

XXX

The rotor of the generator is directly coupled to the rotor of wind turbine.

Mono-crystalline modules with high efficiency (nearly 30%) will be used for

hybrid system. The total module area will be 12 m2. It is almost the same

swept area of the wind generator. The lead acid battery compensates the

difference between the current energy production and current consumption. It

stores energy in the battery when electricity is produced by solar or wind.

Cardona et al., (1999) reported on a general model for sizing a stand-alone

photovoltaic system, using as energy input data, the information available in

any irradiation atlas. The parameters of the model were estimated by

multivariate linear regression. The results obtained from the numerical loss of

load probability size method (LOLP) were used as initial input data of fit the

mode. For this fit there were used daily global irradiation data from 222 US

meteorological stations for the period 1961-1990. The expression proposed

allowed to determine the photovoltaics array size, with a co-efficient is

independent of the used LOLP value. System parameters and mean monthly

values for daily global irradiation on the modules surface were taken as

independent variables in the models. It also shows that the proposed model can

be used with the same accuracy for other locations not considered in the

estimation of the model. They also proposed model, which would allow

calculating the optimum tilts for the array surface taking the latitude into

account as well as the variability of the incident irradiation.

El-Rafey and El-Sherbiny (1988) simplified the technique for predicting the

photovoltaic (PV) array and system performance. A load/solar/weather database for

seven different locations in Egypt was also provided to aid in the necessary

XXXI

calculations. The insolation data had been collected using of home made, resistance

loaded standard so that their responses were linear with insolation level. Mean

temperature and wind speed have been collected or measured on an hourly basis and

averaged to give daily values. Typical values were 30 Ah at 10 h discharge rate, 2.17

V per battery cell, 0.7 as the battery depth of discharge, and the number of batteries

equal to the total numbers of battery cells used. The fraction of the load that is met

by the solar photovoltaic system is calculated for each of the seven locations.

XXXII

Chapter 3

SOLAR PHOTOVOLTAIC SYSTEM

3.1 Introduction

A photovoltaic system consists of photovoltaic module, energy storage,

converter, charge controller and Balance-Of-System (BOS) components. The

solar cells are the heart of a PV system. A typical PV cell produces less than 2

watts at approximately 0.5 volt DC. So, for high power applications,

photovoltaic cells must be connected in series parallel configurations to

produce enough power. A single solar cell or a suitable interconnected matrix

of solar cells when hermitically sealed with a transparent front cover and

durable back cover constitutes a solar PV module. The cells are configured

into modules and modules are connected as array. Modules may have peak

output powers ranging from a few watts to more than 300 watts. Typical array

output power may be of hundred watts to kilowatt range, although megawatt

arrays exist. Fig 3.1 shows the schematic diagram of a photovoltaic system.

The PV cells produce electricity only when it is illuminated i.e. at daytime only as

shown in Fig.3.2 (a). That means PV systems need energy storage so that the captured

electrical energy may be available at nighttime as shown in Fig.3.2 (b). Generally the

storage mechanism consists of rechargeable batteries, but more exotic storage

mechanisms are also available. In addition to storage, batteries also provide transient

suppression, system voltage regulation and a source of current that can exceed PV array

capabilities. Fig. 3.2 (c) shows a system that operates during shortfall.

A charge controller accompanies the battery storage in order to prevent the batteries

from reaching either an overcharged or over discharged condition. Sometimes an

XXXIII

inverter is also needed to convert the DC from battery or directly from PV array to AC

when connected loads are AC load. In case the PV system does not produce adequate

energy, a back up system is incorporated to it and in that case the system will need a

controller to operate the back up system.

Figure 3.1 Schematic diagram of a photovoltaic system

3.2 Systems

PV systems fall into two basic categories: stand-alone and grid linked. The

grid is the low AC voltage electricity supply network, also known as the

‘utility’ or the ‘mains’. Each of these categories is described below:

Solar

Battery

DC Load AC

Controller

Bi-directional

XXXIV

XXXV

Fig. 3.2 Schematic of daily operation of a typical solar-diesel hybrid system

3.2.1 Stand-alone systems A stand-alone PV system is any system incorporating PV modules and not

having a connection to the grid. The simplest stand-alone system consists of a

module supplying a load directly. Such a system is shown in

Fig. 4.3, which can be used to power a pump or to charge a battery.

Fig. 3.3 PV system directly connected to load

Beyond a certain size of system a charge regulator is necessary to protect the

battery from over-charging with subsequent reduction in life. This forms the

basic DC PV system and is illustrated in Fig.3.4. As loads are added the charge

regulator would also serve the function of protecting the battery from over-

discharging.

PV Array DC Load

XXXVI

Fig. 3.4 Basic stand–alone PV system

Further energy generator can be added to contribute charge to the battery resulting in a

‘hybrid’ system, as shown in Fig.3.5. These generators can include diesel generators,

wind turbines or fuel cells.

The diesel generator is usually limited by automatic control to run for short periods at or

near its most efficient operating point to supply large loads, such as washing machines,

and also to charge the battery. Other generators each have their own method of

regulation with the battery PV charge regulator protecting the battery from over-charge

by the PV system and over-discharge by the load.

Fig. 3.5 Hybrid stand-alone PV system

3.2.2 Grid linked systems Grid linked systems are sub-divided into those in which the grid acts only as an auxiliary

supply (grid back-up) and those in which the grid acts as a form of storage or two-way

supply (grid-connected). In these systems surplus energy flows into the grid and energy

deficit is met from the grid. Alternatively, the grid connected PV system energy supply to

the grid can be considered totally separately from building energy demand which is met

from the grid.

XXXVII

In grid back-up systems the grid could be unavailable at meeting the demand so a stand-

alone AC system consisting of PV array, batteries and stand-alone inverter is used, with

changeover to inverter output when the grid supply goes. Fig. 3.6 illustrates the basic grid

back-up PV system.

Fig. 3.6 Grid back-up PV system

In grid connected systems the grid is assumed to be available most of the time and a grid

connected inverter converts the DC output of the PV array to 230V or 400V 50Hz AC for

direct connection to the grid supply without the need for a battery. Fig.3.7 illustrates a

typical grid connected PV system. The disadvantage of the system is the need for the

presence of the grid for the inverter to function; if the grid fails then no energy is generated

even at times of high irradiance.

XXXVIII

Fig 3.7 Grid connected PV system

Four configurations of metering are possible for grid-connected systems:

(i) C-B, A-D, E-F Parallel metering, no demand offset

(ii) C-B, A-D, E-F, C-F parallel metering with demand offset

(iii C-E, E-F Reversible or no metering with demand

offset

(iv) C-B, C-E, E-A Series metering with demand offset.

3.3 The Solar Cell

A typical solar cell is a specially designed p-n junction diode or Schottky

barrier diode. The performance of a solar cell is governed by different

properties of semiconductor materials like band gap, carrier concentration,

mobility etc. The semiconductor materials are characterized as being perfect

insulators at absolute zero temperature; with charge carriers being made

available for conduction as the temperature of the semiconductor material is

increased. The semiconductor materials have an energy band gap (Eg) between

the valence band and the conduction band. The valence band is the highest

occupied energy band, which is completely filled by the outer valence

electrons of the solid at zero Kelvin. The band immediately above the valence

band is called the conduction band, and is empty at zero Kelvin.

Semiconductors can be divided as intrinsic and extrinsic. In intrinsic

XXXIX

semiconductor the density of electron (n0) in conduction band is exactly equal

to the density of hole (p0) in valence band & is equal to the intrinsic carrier

concentration (ni).

i.e. p0 = n0 = ni (3.1)

Extrinsic semiconductors are those, which have been doped with trivalent or pentavalent

material and depending on type of impurity material it is divided into p-type & n-type

semiconductor.

3.3.1 Doping

Doping means introducing a very small amount of impurity, of

the order of one in a million atoms. One can either introduce

donors, i.e., atoms with excess electrons, or acceptors, i.e., an

atom with a lack of electrons. Silicon generally prefers to share

its four valence electrons with four other partners as shown in

the intrinsic case in Fig3.8. The arrangement is a stable

tetrahedral structure. Each Silicon atom has exactly four

neighboring atoms in a very ordered structure.

Fig. 3.8 Illustration of the effects of doping

Boron is a material with three valence elections. Doping with it results, as

shown in Fig. 3.8 in an acceptor, i.e. it can trap free electrons. It leaves so-

missing electron surplus electron

p-type n-type intrinsic

XL

called ‘holes’ in the lattice. These holes are unsatisfied valence electrons.

They act like positive charges. These charges can move through the material

in exactly the same way as an electron. This ‘p-type’ silicon has holes as

majority carriers, i.e. a current are normally carried though hole transport.

Phosphorus, on the other hand, has five valence electrons. It is a donor because it donates the unsatisfied electron easily. Silicon so doped is called ‘n- type’. The majority carriers are electrons.

Holes, like electrons, will move under the influence of an applied voltage but, as the mechanism of their movement is valence electron substitution from atom to atom, they are less mobile than the free conduction electrons.

3.3.2 The p-n junction If a junction is formed between a p-type semiconductor and an n-type semiconductor, the junction is called a p-n junction. Such a system is illustrated in Fig. 3.9. When a junction is formed between n-type and p-type semiconductor, the first thing to happen is that the conduction electrons on the n-side of the junction notice the scarcity of the same on the p-side, and valence holes on the p-side notice the scarcity of valence holes on the n-side. Since both types of charge carrier are undergoing random thermal motion, they begin to diffuse to the opposite side of the junction in search of wide-open space. This diffusion of charge particles constitute a current known as diffusion current given by

Jp = -qDp dp/dx, for holes and (3.2)

Jn= qDn dn/dx, for electron (3.3)

Where Dp and Dn are known as diffusion constant for hole and electron

respectively.

XLI

Fig. 3.9 Schematic diagram of p-n junction including the charge density and

electric intensity

When an electron leaves the n-side for the p-side, however, it leaves behind a

positive donor ion on the n-side, right at the junction. Similarly, when a hole

leaves the p- side for n-side, it leaves a negative acceptor ion on the p-side. If

large number of holes and electrons travel across the junction, large number of

fixed positive and negative ions is left at the junction boundaries. These fixed

ions, as a result of Gauss’s law, create an electric field that originates on the

positive ions and terminates on the negative ions, thus the number of positive

and negative ions is same across the junction.

The electric field across the junction gives rise to a drift current in the direction

of the field. The holes move in the direction of the electric field and electrons

move opposite to holes. The drift current is given by-

J=σE (3.4) Where J represents the current density in A/cm2, σ the conductivity in Ω-1 cm-1 and E the field strength in V/cm.

For both electrons and holes, the drift current component is opposite to the diffusion current component. The drift and diffusion components for each charge carrier must be equal and opposite, since there is not current flow through the junction region. This phenomenon is known as the law of detailed balance. The built in potential across the junction can be shown as,

Vi = kT/qln (pn0/np0) (3.5)

Considering pn0 ≈ ND and np0 ≅ ni2/NA , we get

Vi = kT/qln (NA ND/ ni2) (3.6)

Where ND is the donor doping density, NA is the acceptor doping density. The

concentration of holes (p = pn0 in equilibrium) which are the minority carriers

XLII

in n-type semi-conductor is many order of magnitude smaller than the electron

(majority carrier) concentration and is given by

pn0 = ni2/ND (3.7)

Again n=np0 is the minority carrier (electron) concentration in equilibrium in p-

type semiconductor and given by

np0 = ni2/ND (3.8)

The magnitude of intrinsic carrier concentration is given by

ni2 = pono

i = NcNve-Eg/kT (3.9)

Where, Nv and Nc are constants known as valence band effective density of

states and conduction band effective density of states respectively.

NV = 2(2πmh * kT/h2)3/2 (3.10)

Nc = 2(2πmc * kT/h2)3/2 (3.11)

Where mh,, mc are effective mass of hole and electron respectively. Another important parameter is Fermi level, which in intrinsic semiconductor is situated near middle of the band gap, with a small offset caused by the difference between the effective densities of states in the valence and conductions. Basically Fermi level is the highest occupied energy level in a semiconductor & is given by

EF = (EV+EC) / 2 + kT / 2 ln (NV/NC) (3.12)

Where,

EC = Conduction band edge energy,

EV = Valence band edge energy.

The Fermi level in doped semiconductor (n-type) is very close to the

conduction band edge energy and is given by

XLIII

EF = EC - kT ln (NC/ND) (3.13)

The respective parameter for a p-type semiconductor is

EF = EV + kT ln (NV/NA) (3.14)

Here the Fermi level lies very close tot he valence hand band edge.

3.3.3 The volt-ampere characteristics

The current, ID in a p-n junction is related to the applied voltage V by the following

equation.

ID = I0 [e (v/η) V

T -1] (3.15)

Where, I0 is the reverse saturation current and VT is the volt equivalent of temperature and it

is given by:

VT = KT / q = T/11600 (3.16)

Where,

T is the temperature in degree Kelvin.

Positive value current, ID implies that current flows p-side to n-side, if V is positive, the

diode is forward biased signifying that the p-side is positive with respect to the n-side. The

symbol η is 1 for germanium diode and is approximately 2 for silicon diode at rated

currents.

Fig. 3.10 shows the volt- ampere charlatanistic of a typical diode and follows the equation

(3.15). With applied voltage V positive and several times VT, the unity within the bracket in

equation (3.15) may be neglected. Hence the current, ID, increases exponentially with

voltage V except for very small values of V, with the diode reverse biased and |V| several

times VT, current ID approximately equals I0. The reverse current is thus constant,

XLIV

independent of the applied reverse bias. This is the reason why IO is called the reverse

saturation.

Fig. 3.10 Volt- ampere characteristics of an ideal p-n diode

To display the forward and reverse characteristics more clearly, we may use two different

scales for forward and reverse currents. Fig.3.11 shows the forward current in milli-amperes

and the reverse current in microamperes. The dotted portion of the reverse current curve

shown that at reverse voltage VZ, the reverse current no longer follows equation (3.15) but

increases abruptly. At this critical voltage, a large reverse current flows and breakdown is to

take place.

Fig. 3.11 Volt- ampere characteristic of an ideal p-n diode with expanded scale for reverse current

I0

I

V

VZ

V,V

μA

I,mA

5 4 3 2 1

6

1.0 0.5

XLV

3.3.4 Generation of electron-hole pair by photon absorption

According to Einstein quantum theory, light is composed of quanta of energy known as

photon. The energy of each photon is given by

E = hc/λ in joules (3.17)

Where h is the Plank’s constant, h = 6.63 x 10-34 joules-sec, c is the velocity of

light equal to 2.998 x 108 m/sec, λ is the wave length of light expressed in

meters.

E=1.24/λ in eV (3.18)

In order to be absorbed a photon must have energy greater than the band gap energy (Eg).

Photons with energy in access of the band gap can be converted into electricity. If a photon

has energy greater than the band gap it still can produce only a single electron hole pair

(EHP), the remaining energy being lost to the cell as heat.

3.4 Technical Aspects of Solar Cells

3.4.1 I-V characteristic of solar cells

When a load is connected to an illuminated solar cell, the current that shows is

the net result of two counteracting component of internal current:

(a) The photo generated current or simply photocurrent, IL, due to

generation of carriers by the light.

(b) The diode or dark current, ID, due to the recombination of carriers

driven by extended Voltage, This voltage is needed to deliver power

to the load.

Let us assume these two carriers can be superimposed linearly and this

is true in for many practical cases. Then the current in the external

XLVI

circuit can be calculated as the difference between these two

components. Thus, we can write,

I = IL-ID ( V) (3.19)

If we assume that in the diode can be expressed by a single exponential

equation, then the characteristic equation for the device is

I = IL- I0 [ exp [( eV / mkT )-1] (3.20)

The I-V curve represented by this equation is shown in Fig.3.12

Fig.3.12 Illuminated I-V characteristics

5

-0.2 0 0.2 0.4 0.6 0.8 1.0 1.2

15

10

30

25

20

0

-5

Voltage, (V)

Cur

rent

den

sity

(

mA

/cm

2 )

XLVII

3.4.2 Short- circuit current and open-circuit voltage

As seen from Fig 4.12, the greatest value of current with the cell as a

generation (in the first quadrant) is obtained under short- circuit conditions,

when V=0. According to equation (3.19) the short circuit current Isc, is given

by

Isc ≡ I (V=0) IL (3.21)

If the device is kept in open-circuit, so that I = 0, it biases itself with a voltage that is the

greatest that can arise in the first quadrant. This is called the open circuit voltage Voc. Its

value is such that the photocurrent is completely cancelled by the bias current, that is to say

IL = ID(VOC) under open-circuit conditions. Then from equation (3.23), we find:

VOC = mkT / q ln [IL / I0 + 1] (3.22)

The definition of the above two operating parameters allows as the alternative

form of characteristics curve:

I=ISC [1-exp (-e (VOC-V / mkT) (3.23)

This form is sometimes useful. The formula is accurate about the open-circuit point, but its

viability for the whole working range its questionable since the parameters m and I0 of

equation (2) depend, to some extent, on the position on the curve.

XLVIII

3.5 Effect of irradiation

The cell current is directly proportional to the cell irradiance. Thus if the cell

current is known under standard test conditions G0=1 kw/m2 at 1.5 AM, then

the cell current at any other irradiance, G, is given by

IL (G) = (G/Go) IL (Go) (3.24)

Where IL = the component of cell current due to photons.

The I-V characterististics of solar cell under different illumination levels is

shown in Fig. 3.13

Fig. 3.13 I-V characteristics of solar cell under different illumination levels

3.6 Effect of Fill Factor

The fill factor is a measure of the quality of the cell. Cell with large internal resistance will

have smaller fill factors, while the ideal cell will have a fill factor of unity. Typical FFs for

real solar cell may vary from 0.5 to 0.82. The secret to maximizing the fill factor is to

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0

3-

2-

1-

1 kw/m2

750 w/m2

500 w/m2

250 w/m2

Cel

l Cur

rent

, A

Cell Voltage, V

Real Cell

XLIX

maximize the ratio of photocurrent to reverse saturation current while minimizing series

resistance and maximizing shunts resistance within the cell.

3.7 Effect of Temperature

The PV cell I-V & P-V curve is temperature sensitive. The open circuit voltage is

directly proportional to the absolute temperature of the cell. The reverse saturation

current is also highly temperature dependent. The net result is that the open circuit

voltage of a silicon PV cell decreases by 2.3 mV for each degree Celsius (°C) increase

in temperature. The temperature dependence of PV curve of solar cell is shown in Fig.

3.14.

Fig. 3.14 Temperature dependence of PV curve of a solar cell

3.8 Radiation Absorption and Material Selection

The interaction of radiation with different materials is characterized by the

absorption coefficient ∞. The variation of ∞ with photon energy is as shown in

Cell Voltage, V

Cel

l Pow

er, W

0 0.2 0.4 0.6

0

0.5

1.0

1.5

2.0

50ºC 25º C

0ºCX C

-25º C

L

the Fig.3.15. The absorption edge is determined by the energy band gap of the

material. The nature of the band gap also affects the efficiency of absorption in

the material. Depending upon the nature of the band gap the semiconductor

materials are divided into direct and indirect band gap materials. The direct

band gap materials e.g. GaAs, CdTe and amorphous silicon absorb photons

much more rapidly than the indirect materials, such as crystalline silicon. As a

result, the direct band gap material does not need to be nearly as thick to

absorb a significant part of the incident radiation.

Fig. 3.15 Variation of á with photon energy for different semiconductors

0 0.5 1.0 1.5 2.0 2.5 3.0

103

104

105

106

CuInSe2

GaAs

CdTe

C-Si

a-Si

hv [eV]

α [V

cm]

LI

According to Beer’s law describing the penetration of radiation through

matter, we have

I(z) = IJ (I-r)e - dz (3.25)

Where Ij is the irradiance, r is the reflection coefficient at the surface, and the

direction of penetration. The absorption coefficient ∞ determines the r equired

thickness of photovoltaic layers. Let ∞ be in the order of 5, which express that

within the thickness more than 99% of the radiation is absorbed, then this

absorption depth describes the thickness of the absorber material.

Zs=Lá=5/∞ (3.26)

LII

It can be reduced by the use of reflecting back surfaces. Whereas crystalline Si solar

cells require thickness ranging between 50 and 100 µm, cells consisting of direct band

gap semiconductor or amorphous Si can be realize with thickness below 1µm. The use

of direct semiconductor implies a substantial reduction of material and leads to the

concept of thin film solar cell.

3.9 Maximizing of Solar Cell Performance

The following steps can maximize the performance of a PV cell:

• Minimizing the reverse saturation current

• Optimizing photocurrent

• Minimizing reflection of incident photons

• Maximizing minority carrier diffusion length

• Maximizing junction width

• Minimizing surface recombination velocity

• Minimizing cell resistance losses.

3.10 The PV Module and Array

In a module, a number of cells are connected together in series that shown in Fig. 3.16.

The electrons flow from one cell into conductors that carry them to next cell. In that cell

they are once again struck by photons, being lifted to a higher potential energy and

swept out of the cell. Finally electrons leave the last cell in the module and flow to the

load. As soon as an electron leaves the last cell in the module and enters the wire, an

electron at the other end of the wires moves into the first cell in the module. So, a PV

cannot run down like a battery nor produces electricity in response to light. A PV cell

cannot store electrical energy; it can only convert light energy into electrical energy.

Since PV systems are commonly operated at multiples of 12 volts, the modules are typically

designed for optimal operation in these systems. The design goal is to connect a sufficient

LIII

number of cells in series to keep Vm within a comfortable range of the battery and system

voltage under conditions of average irradiance.

When the module is not illuminated then it can be considered as a series connection of

diodes that may be forward biased by the system shortage batteries. To prevent the

current from flowing in the reverse direction a diode is connected in series with the

module. This blocking diode has forward voltage drop and associated with power loss of

more than 1 Watt when the module is providing photocurrent. Again shading of

individual cells may result heating of the cell and this phenomenon can cause premature

cell failure. To protect the system against such failure, arrays are generally protected

with bypass diodes.

Fig 3.16 Photovoltaic Module

The cells in a module are covered with anti-reflective coating, then with a

special laminate to prevent degradation of the cell contacts. The module

housing is generally metal, which acts as a heat sink for the heat generated in

the modules from the fraction of absorbed sunlight not converted to electricity.

+ – Silicon photovoltaic ll

Silicon photovoltaic cells

DC electricity

Frame (plastic or metal)

Sun

LIV

When the PV cells are mounted in a module, they can be characterized as

having a Nominal Operating Cell Temperature (NOCT). The NOCT is the

temperature that the cells will reach when they are operated at open circuit in

an ambient temperature of 20°C with G=0.8 kW/m2 and a wind speed of less

than 1 m/s. For variations in ambient temperature and irradiance the cell

temperature (in °C) can be estimated quite accurately with the help of

following relation:

TC = TA +G (NOCT-20) / 0.8 (3.27)

The cells in a module being series connected must be matched as closely as possible. If this

is not the case, while some cells are operating at peak efficiency, others may not be

optimized. As a result, the power output from the module will be less than the product of the

number of the cells and the maximum power of one single cell.

To obtain higher voltages or currents than are available from a single module are

required, modules must be connected into arrays. Series connections result in higher

voltages, while parallel connections result in higher currents.

3.11 Energy Storage

PV cell can generate electricity under illumination only. So for nighttime application energy

storage is a must. The most common energy storage is Lead Acid Storage Battery. This is

relatively economical storage of relatively large quantities of electrical energy. Basic

properties of lead acid storage batteries shown in Table 3.1.

Table 3.1 Properties of lead acid storage battery

State of Charge Specific Gravity Cell Voltage Voltage of 12 Freezing

LV

(SOC) (%) (V) V Battery Point 0F

100% 1.265 2.12 12.70 -71

75% 1.225 2.10 12.60 -35

50% 1.90 2.08 12.45 -10

25% 1.155 2.03 12.20 +3

0% 1.120 1.95 11.70 +17

Source: (Messenger, 2000)

3.12 Associate Electronic Components

3.12.1 Charge controller

In nearly all system with battery storage, a charge controller is an essential component. The

charge controller controls the charging and discharging process of the battery. The charge

controller cuts off the load when the battery reaches a prescribed state of discharge.

3.12.2 Inverter

An inverter converts DC current into AC current. Depending upon the requirements of the load, a number of different types of inverters are available. Selection of the proper inverter for a particular application depends on the waveform requirements of the load and on the efficiency of the inverter. Inverter selection will also depend on whether the inverter will be a grid connected system or stand-alone system. Inverter failure is one of the PV system failures. Different inverters with their specification are given in the following Table 3.2.

Table 3.2 Summary of inverter performance

Parameter Square wave Modified sine

wave

Pulse Width

Modulated

Pure Sine

wave

Output Power

Range (watts)

Up to

10,00,000

300-2.500 Up to

20,000

Up to 2,000

Efficiency 70-98% 70-85% > 90% Up to 80%

Source: (Messenger, 2000)

3.13 Balance of System Components

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The Balance-Of-System (BOS) components include mounting materials for the

modules, wire and all wiring components, lighting protectors, grounding

connections and battery containers. BOS can be divided into two categories-

power related BOS and area related BOS. The area related BOS includes

module support structure, foundations, electrical wiring and control elements

for the system. The power related BOS are power conditioning unit (inverter,

controller, maximum power taker etc), metering and safety provisions.

LVII

Methodology CHAPTER 4

4.1 Optimal Design Using Genetic Algorithm

A PV-diesel hybrid system has a greater reliability for electricity production

and least costly than the systems that use a single source of energy. When

designing a hybrid system both the sizing of the elements and the most

adequate control strategy must be obtained. Obtaining a good control strategy

is essential, since the performance of a PV hybrid system can be significantly

affected by relatively small changes made in the control strategy. The optimal

design of such a system can not be achieved easily using classical optimization

methods. Genetic Algorithms (GA) appears to be the adequate search

technique for such complex problems.

The Genetic Algorithm (GA) is a global optimization method based on the

principle of survival of the fittest Darwin's hypothesis of evolution. The basic

principles of the GA are attributed to Holland (1975) and further developed for

engineering applications by Goldberg (1989) and Michalewicz (1996).

Genetic algorithms simulate the phenomena of reproduction, selection,

crossing and mutation that are observed in nature using a computer program.

GA may manipulate a population of candidate solutions to a problem. The

candidate solutions are typically binary strings, but any representation may be

used. At every generation some of the candidate solutions are paired and parts

of each individual are mixed to form two new solutions; this is crossover,

uniform crossover exchanges individual bits whereas multi-point crossover

exchanges whole substrings. Additionally every individual is subjected to

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random change - mutation. The next generation is produced by selecting

individuals from the current one on the basis of their fitness, which is a

measure of how good each candidate solution is. Eventually the population

should become saturated with individuals of very high fitness.

The PV-diesel system is studied using an hourly time step for one hour. Every

hour the following inputs are estimated: the current from PV which depends on

solar insolation, the ac load current which depends on predicted load and the

battery state of charge (SOC).

The GA used here is divided into two parts: main algorithm and secondary

algorithm. The main one searches for possible component configurations of

the hybrid system whereas the secondary one searches for the best strategy for

each of the configurations found in the main algorithm. The main algorithm

works with an integer vector with the number of PV in parallel, the solar

generator type code (PV panel), the battery type code, the number of batteries

in parallel and the diesel generator type code. The secondary algorithm works

with a Boolean vector with the dispatch strategy.

The main requirements for system design are:

(i) The site information (environmental data), such as solar intensity,

ambient temperature, relative humidity and cloudiness should be collected.

(ii) The electrical load information such as the load type and time of use of

electrical appliances should be identified.

LIX

(iii) The specifications and cost information of solar panel, battery, inverter,

charge regulator and diesel ac generator set.

There is a "Frugal" option that can be applied in all the strategies, The critical

discharge load (Ld) is the net load above which the marginal cost of generating

energy with the Diesel generator is less than the cost of drawing' energy out of

the batteries. If the Frugal option is applied, then the Diesel generator meets

the net load whenever the net load is above the critical discharge load,

regardless of whether or not the battery bank is capable of meeting the net

load.

The cost of generating energy with the Diesel generator and the cost of

drawing energy out of the batteries are equal when the net load is Ld:

B. PNgen Prfuel + Co &Mgen + Crep-gen-h + A. Prfuel Ld

=Ccycling-bat Ld

ηinv (4.1)

then, Ld can be calculated as follows:

Ld =

Pgen is the Diesel generator acquisition cost plus O & M cost throughout Diesel

generator lifetime (Є) and Lifegen is the Diesel generator lifetime (h). Ccycling_bat

(Є/kWh) is the cost of cycling energy through the batteries.

B. PNgen Prruel + Co &Mgen + Crep-gen-hCcycling_bat-ηinv. A. Prfuel

(4.2)

where CO&Men is the Diesel generator's hourly operation and maintenance cost

(Є/h), Prfuel is the fuel price (Є/I).

A = 0.2461/kWh and B = 0.84151/kWh are the fuel curve coefficients. The fuel

cost of 1 h Diesel running, Cfuel (Є) is,

Cfuel = Prfuel . (B. PNgen + A. Pgen) (4.3)

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Ccycling_bat = Cbat

CN . Nbat_p . UDC . Ncycles_eq ?1000

The Critical Charge Load is the net load where the cost of generating, this load

with the Diesel generator (exactly this load and no more) for 1 h is the same as

(4.4)

Cbat is the batteries bank acquisition cost plus O&M cost throughout batteries

lifetime (Є), CN is the nominal capacity of one battery (Ah), Nbat_p is the

number of batteries in parallel, and Ncycles_eq is the number of full cycles of

battery life. We have assumed that the batteries can cycle a certain amount of

energy, which divided by its nominal capacity, gives the equivalent cycles (full

cycles). It is true that the energy that a battery can cycle depends on the depth

of discharge, but is almost constant if the discharge is never allowed to fall

below SOCmin, this being greater than 20%.

4.1.1 Cycle charging strategy

If the batteries cannot meet the net load, the Diesel. generator runs at full

power (or at a rate not exceeding the maximum energy that batteries are

capable of absorbing) and charges the batteries with any surplus power. If a

SOC set point is applied, the Diesel generator will continue running until the

batteries reach this SOC set point.

The Frugal option also can be applied in this strategy.

4.1.2Combined strategy

This strategy combines both strategies. If the net load is lower than the

Critical Charge Load, Lc, (kW), the Cycle Charging strategy is applied. If the

net load is higher than L, the load Following strategy is applied.

/

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the cost of supplying this load, for 1 h, with the batteries that have been

previously charged by the Diesel generator. Mathematically this is:

B. PNgen . Prfuel + Crep_gen_h + A . Prfuel . Lc

=A.Prfuel . Lc

ηch . ηinv +

Ccycling-bat Lc

ηinv (4.5)

Where Lc is

Lc = ηch . ηbat PNgen Prruel + Co &Mgen + Crep-gen-h

ηch . ηbat Ccycling_bat-ηinv. A. Prfuel

(4.6)

Where ηbat is the battery efficiency in the charging process.

The Frugal option also can be applied in this strategy.

4.2 Genetic algorithm

The problem to be solved has a great number of possible solutions

(combinations of solar generator, batteries, Diesel generator and strategy

variables), and it is difficult to solve this problem with classical mathematical

techniques.

The Genetic Algorithms technique works with individuals (possible solutions).

A vector whose components represent the parameters of the system using an

integer code can represent an individual.

The GA developed in HOGA by Dufo-Lopez et al. (2005) is divided in two

parts: main and secondary algorithm.

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4.2.1 Main algorithm

The main algorithm works with an integer vector with the number of PV

panels in parallel (4 the solar, generator type code (PV panel) (b), the battery

type code (c), the number batteries in parallel,(d) and the Diesel generator type

code (e): |a|b|c|d|e|.

Each solar generator is from a different manufacturer and their characteristics

are: power, voltage and acquisition cost.

Each battery is from a different manufacturer and their characteristics are:

rated capacity, voltage, acquisition cost, DODmax number of equivalent cycles

and efficiency.

Each Diesel generator is from a different manufacturer and their characteristics

are: power, voltage, acquisition cost, lifespan, minimum output power, and

O&M hourly cost.

The algorithm simultaneously uses Nm vectors such as the one described

beforehand.

The main algorithm obtains the optimal configuration of PV panels, batteries

and Diesel generator, minimizing the Total Net Present Cost of the system

(CTOT), which includes all the costs throughout the useful lifetime of the

system, which are translated to the initial moment of the investment using the

effective interest rate, according to' standard economical procedures.

CTOT = CSEC + CACQ-PB + CACQ-B + CACQ-BCH

+ CACQ-GEN + CREP-BCH + CO&M_PV + CO&M_B (4.7)

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Where CSEC includes the costs that depend on the optimal strategy. It is

evaluated in the secondary algorithm, explained CACQ-PV, CACQ-B, CACQ-BCH

CACQ-GEN are the costs of the acquisition of the PV panels, the batteries, the

battery charger and the Diesel generator. CREP-BCH is the cost of replacing the

battery charger throughout the life of the system (it does-not depend on the

strategy because we assume it has fixed initial cost and life). CO&M_PV, CO&M_B

are, respectively, the costs of maintenance of the PV panels and the batteries

(they do not depend on the strategy). CTOT must be calculated for each

combination, represented by one of the Nm vectors which constitute the

population.

The fitness function of the combination i of the main algorithm is assigned

according to its rank in the population (rank 1 for the best individual

considering the objective function, and rank Nm for the worst solution),

FitnessMAIN = (Nm + 1) - i

Σj [(Nm + 1) - j] , j = 1 ………. Nm (4.8)

4.2.2 Secondary algorithm

The secondary algorithm works with a Boolean vector with the dispatch

strategies (Cycle Charging or Combined), the "Frugal" option, and 5 bits that

represent the SOC set point in Gray code (better than binary code for GA):

|Stmtegy|Frugal|go|gl|g2|g3|g4|.

The Load following strategy is evaluated at the end, as this strategy has no

SOC set point.

The algorithm use Nsec vectors such as the one previously described.

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For each vector of the main algorithm, the optimal strategy is obtained

(minimizing the non-initial costs, including operation and maintenance costs,

CSEC) by means of the secondary algorithm.

CSEC = CACQ-INV + CACQ-REG + CREP-B

+ CREP-INV + CREP-REG + CREP-GEN

+ COKM-GEN + CFUEL (4.9)

where CACQ_NV, CACQ_REG are the acquisition costs of the inverter and the

charge regulator respectively (the inverter maximum power and the charge

regulator current depend on the strategy, so their cost must be here). CREP-B,

CRWJNV, CREP-REG, CREP-GEN are the Costs of replacing the batteries, the inverter,

the charge replator and the Diesel generator throughout the life of the system.

CO&M_GEN is the cost of operation and maintenance of the Diesel generator

throughout the life of the system. CFUEL is the cost of the fuel consumed

throughout the life of the system.

We assume that the system life is the life of the PV panels which are the

elements that have a greater lifetime.

The fitness function of the combination i of the secondary algorithm is

fitnessSECi, = (Nsec + 1) - i

Σj [(Nsec + 1) - j] , j = 1 …………. Nsec (4.10)

4.2.3 Implementation of the GA

HOGA has been implemented in the following way:

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1. Initially, Nm vectors are obtained randomly from the main algorithm. These

vectors have been described in 4. 1, each one representing a possible

configuration of PV panels, batteries and Diesel generator.

2. For each vector N. of the main algorithm, the secondary algorithm is

executed, obtaining the optimal dispatch strategy for each Nm vector:

2.1. Nsec vectors are obtained randomly from the secondary algorithm. These

vectors have been described in 4.2, each one representing a possible dispatch

strategy.

2.2. The Nsec vectors are evaluated by means of their aptitude .

2.3. The best vectors (fittest) have a greater probability of reproducing

themselves, crossing with other vectors. In each cross of two vectors, two new

vectors are obtained (descendents). The descendents are evaluated and the best

of them replace the worst individuals of the previous generation (iteration).

2.4. To find the optimal solution and not to stay in local minimal, some

solutions randomly change some of their components (mutation). The

mutations can effect the change of the control strategy or the change of a bit of

SOC set point.

2.5. The individuals (vectors) obtained from reproduction and mutation are

evaluated, making the next generation.

2.6. The process continues (from 2.2 to 2.5) until a determined number of

generations (Ngen_max) have been evaluated.

3. Nm solutions will have been obtained (vectors of the main algorithm

with their optimal dispatch strategies). The Nm solutions am evaluated by

means of their aptitude.

LXVI

4. Reproduction, crossing and mutation are carried out on the obtained

solutions, making the next generation.

5. The process continues until a determined number of generations have been

evaluated. The best solution obtained is that which has the lowest value of

CTOT.

The flow diagram of the algorithm is represented in Fig. 4.1.

Fig. 4.1 Flowchart of HOGA

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4.3 Case study: Sandwip-an Isolated Island

Sandwip is a small island in Bangladesh, which is totally disconnected from the main land.

The island is situated in a very remote area and lacks both an electricity supply and modern

facilities. But the island has great potential for developing electricity from solar energy.

This case study examines how decentralized, small–scale, community-based power can be

generated.

4.3.1 Characteristics of the island-Sandwip

(a) Location and population: Sandwip is a deltaic island in the Bay of Bengal region of

Bangladesh, adjacent to Chittagong and a mere 15 km from, the main land. The population

is around 330,000 on an area of 240 km2. The entire Island is a mudflat created from the

Ganges (Fig.4.3).

(b) Natural hazards: The island is situated in the middle of the Meghna estuary where

strong storm surges propagate deep into mainland through the river channel. The storm

surges height is higher than at any other part of coastal Bangladesh. Thus, the coast of

Sandwip is very vulnerable to cyclones and flooding.

(c) Infrastructure: Sandwip is one of the oldest islands in the Chittagong region. Most of

its natural and historical heritage has been drowned in the Meghna River through the

erosion process. Most of there people are very poor. Therefore, apart from some private

building, most of the concrete

LXVIII

Fig. 4.2 The location map of Sandwip, Bangladesh

buildings on the island belong to the government including the multipurpose cyclone

shelter.

LXIX

(d) Electricity characteristics: Most of the energy in Sandwip is derived from fossil fuel

(mainly from biomass, coal and oil) which is not a good option for sustainable development.

However, in common with the predominantly agro-based population of the rest of

Bangladesh, bio-fuel is mostly used for cooking in Sandwip. On the other hand, lighting

needs are met by using kerosene. Expenditure of lighting is minimized by short evening

hours and limited nighttime activities. A short electricity grid is available linking the main

commercial areas on the island. (Shahjahan, 2004).

Therefore, the opportunities for expansion of electricity-based industry are limited. In this

context, the need for developing energy, in particular solar-diesel hybrid power generation

system carries a greater sense of urgency on this island.

(e) Lifestyle characteristics: The humane-resource relationships that operate at present

Sandwip are characterized by:

(i) Widespread poverty, limited livelihood opportunities;

(ii) Poor levels of service provision and very poorly developed institutional structure;

(iii) Highly unequal social structure, high levels of conflict and poor law and order;

(iv) A few powerful people dominate the mass of the coastal population;

(v) Rapid decline in common resources;

(vi) The constant threat of cyclones and storm surges;

(vii) The long-term effects of climatic change;

(viii) Widespread pollution and resources degradation; and

(ix) Very poor access to infrastructure and technology.

(f) Communication characteristics: The Island has a very poor transportation system in

most of the areas. Lack of good transport blocks the growth of trade and commerce.

Traditional bullock cart is used as the main vehicle. Besides road communication, there is

no electro-communication system, except walkie-talkie and a very poorly managed

telephone system

4.3.2 Energy requirements in the community

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The household in rural Bangladesh is simple and does not require a large quantity of

electrical energy for lighting and electrical appliances. Salequzzaman (2003) estimated 20

kWh for about 132 families in the island Sandwip. Monthly average daily load profile

illustrated in 4.3. The average daily solar radiation varies from 6 kWh/m2 to 4 kWh/m2 with

average value of 4.3 kWh/m2. The standard deviation is 0.67 shown in Fig. 4.4.

Fig. 4.3 Monthly average daily load profile

Figure 4.4 Average daily solar radiations.

LXXI

4.4 Design Layout

The design layout of the distribution system of a solar diesel hybrid system in

Sandwip is shown in Fig. 4.4 (Bala, 2004).

Fig. 4.5 Schematic diagram of batteries in series and parallel connection

+

Solar panel

LXXII

CHAPTER 5

RESULTS AND DISCUSSION

The system has been designed and optimized using the software HOGA

developed by Dufo-Lopez et al. (2005)

The parameters considered are: cross over rate, 0.9 and mutation rate 0.01. Maximum number of different PV panel in parallel is 35. Maximum number of different batteries in parallel is 20. The daily load profiles are represented by a sequence of powers, each considered as constant over a time-step of one hour.

The effective interest rate considers is 10 %. The O&M cost of the system is 7 %. The system life time 25 years and Installation cost is 1500 € according to the present local market cost.

5.1 The optimized system configurations

4 PV panels serials × 25 panels parallel 125 Wp, 4 Batteries serials× 9 batteries parallel Cn= 96 Ah, 230 V 1.9 kVA AC generator and 3300 VA inverter. The system supplies 48 V DC and 230 V AC.

The Additional data for PV panel fixed operational and maintenance costs

is 40 €/year. Loss factor is 1.2, Annual inflation rate for PV panels Cost is

4% and maximum variation of PV panels cost is 20 %.

The fixed operating cost are independent of the number and the type of PV panel use for the photovoltaic generator. Fixed operator overheads and cost for maintenance materials are included regardless of the size of the generator.

HOGA calculates cycled energy throughout battery life for each

discharge. Depth-life cycles pair; since batteries will not operate for high

depth.

LXXIII

Capacity batteries varies from 43Ah to 462 Ah and the cost of the

batteries varies 20%. Fixed operational and maintenance cost (O&M) 50

€/year. Annual inflation rate is 4 %.

The inverter selected has a rated output power is 3300 VA. The hourly average output power is 6.9 % of the rated output power of the selected inverter. The average efficiency is 85.4 %.

Auxiliary equipment includes battery charge regulator and AC/DC

converters (rectifiers) are used in the system. Both equipment lifetimes

are 10 year and efficiency is 90 %. State of charge (SOC) of the batteries

and minimum power of the ac generator are 40% and 1,368 W

respectively.

5.2 The control strategies

If the power produced by the renewables is higher than the load, the

batteries are charged with spare power from the renewables. If the power

produced by the renewables is lower, the power not supplied to meet the

load is supplied by batteries (if they can not supply the whole, the rest will

be supplied by the ac generator).

The results were obtained with the following values: main algorithm generations 50;

population 20 and secondary generations 25 and population 10. Figure 4 shows the

evolution of the best total net present cost as a function of the main algorithm

generations in an optimization where the number of generations in the main

algorithm is 50 and the net present cost is 135,638 Euro. Also the emission is 548 kg

CO2

LXXIV

Figure 5.1. Total net present cost and emissions a function of the main Algorithm generations. Figure 5.2. Shows the power generation capacity of the PV generator, ac generator and inverter. The component capacity of the PV generator, ac generator and inverter are 12.5 M, 1.9 kVA and 3.30 kVA respectively. The PV generator is the single largest unit responsible to supply the electricity.

Fig. 5.2. Power generation capacity of the PV generator and inverter

Figure 5.3. Shows the annual energy balance of the hybrid PV-diesel

system. Total load and energy charged by the battery are supplied by

solar PV system and ac generator. The major share of the energy (10,890

kWh) comes from solar PV while the contribution of diesel generation is

very small (664 kWh).

12.5

1.9

3.3

0

2

4

6

8

10

12

PV Gen. INV

Pow

er (k

W)

LXXV

Fig. 5.3. Annual energy balances the hybrid system

Figure 5.4. Shows the costs of the different elements of the hybrid PV-diesel system as a percentage of the total net present cost. Batteries cost 15% of the total net present cost. The item others have the least share of 2% and the PV panels are the most expensive elements at 67%. Thus, the cost of PV panels is the most important leverage point where action program is essential for reduction of the production cost of solar panels.

Fig. 5.4. Cost of the different elements of the hybrid system as percentage of

the total net present cost

PV67%

Inverted + AUX8%

Batterys 15%

AC gen. fuel8%

Others 2%

PV

Inverted + AUX

Batterys

AC gen. fuel

Others

7475

1072

10890

664

4563 4579

0

2000

4000

6000

8000

10000

12000

Total load Exc. PV AC Gen. C. Battery D. Battery

Ene

rgy

(kW

h)

LXXVI

CHAPTER 6 CONCLUSIONS

An optimization of PV-diesel hybrid systems for mini-grid for an isolated

island - Sandwip in Bangladesh using genetic algorithm is presented.

It gives the best solution of all possible combinations, finding the best solution

with the help of GA. It gives the number of PV panels and its type, and the

number of batteries in parallel and their type, the number of generator and their

type and number of Inverter and its type.

This study reveals that the major share of the cost is for PV panel-Inverter and technological development in solar photovoltaic technology would make rural electrification in the isolated islands more promising and demanding.

It is clear that human life can be sustained on earth in future only if, within a

short period, we are able to replace conventional energy sources with an

alternative source of energy. Solar energy in general and solar PV in particular,

constitutes such a potential alternative. Solar energy utilization currently has

many deficiencies. However, such deficiencies cannot remain permanent in

front of human ingenuity and intelligence.

The goal for the century ahead must be the complete substitution of

conventional sources of energy by constantly available solar energy - in other

words, a complete solar energy supply for humankind.

LXXVII

GLOSSARY

AC

An acronym for alternating current; the electric current that reverses its direction 50

times and the frequency in Bangladesh is 50 Hz.

Array

An appropriately interconnected combination of PV panels installed outdoors in the

field or rooftop.

Azimuth

Horizontal angle measured clockwise from true north; 180° is due south.

Balance-of-system (BOS)

All mechanical, electrical and electronic components and subsystems in a PV system

taken together, other than the PV array and the storage battery.

Cycle battery The cycle consisting of charging and discharging of a storage battery. [[

DC

Direct current; electric current that always flows in the same direction, positive to

negative. Batteries and solar cells are both dc devices.

Grid

LXXVIII

A term generally used to designate the electrical utility distribution network. However,

with reference to a solar cell, the grid describes the metallic contact pattern on its top

surface.

Insolation

An acronym for Input solar radiation; generally expressed in the energy units of kWh

per m2.

Inverter

An electronic equipment that converts direct current (dc) electricity to alternating

current (ac).

Irradiance

The power of instantaneous solar radiation incident on a surface; generally expressed

in units of kW per m.

Module

An appropriately interconnected combination of solar cells with two output terminals

when hermetically sealed with a front transparent cover. A module is the smallest

energy building block available to the user of solar photovoltaic.

Panel

An appropriately interconnected combination of a number of PV modules on a solid

frame structure. Even one single module on a frame may constitute a panel.

PV

An acronym for photovoltaic (adjective) or photovoltaic (noun).

LXXIX

Rectifier

A two-terminal device, made of an appropriate semi-conductor material like silicon,

which has a unidirectional current carrying characteristic. Also known by the name of

diode.

Solar battery

The term was coined during the 1950’s to designate silicon solar cell. It appears to be a

misnomer because the word battery normally refers to a device that can store energy.

Although solar cells convert sunlight into electricity they cannot store the generated

energy. However, referring a solar cell as solar battery is in general practice even now.

Wp

An acronym to designate the peak watt or watt peak in solar photovoltaic. It represents

the unit to denote the capacity of a solar cell, module, panel or an array at STC. while

kWp designates kilo watt peak, MWp designates mega or million watt peak.

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NOMENCLATURE

A = Cost for a group of batteries

Ac = Auxiliary cost

B1 = First group of batteries

BC = Cost of first group of batteries

BCC = Battery charge controller

d = Discount rate (%)

DOD = Allowable depth of discharge for battery

EL = Electrical load, kWh/day

GA = Genetic Algorithms

H = Average solar energy input/day (kwh/m2/day)

HOGA = Hybrid optimization by genetic algorithms

i = Annual inflation rate (%)

Ic = Inverter cost

Ic = Initial cost

ICPV = Initial cost of PV system

INc = Installation cost

LCC = Life cycle cost

MToe = Mega ton of oil equivalent

N = Life time (years)

n = Day of the years

Nc = Number of continuous cloudy days

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NOMENCLATURE(Contd.)

NREL = National renewable energy laboratory, USA

OMc = Operation and maintenance cost

Pe = Electrical power (Watt)

PSI = Peak solar intensity at the earth surface (1000W/m2)

PVac = PV array cost

PW = Present worth

SOC = State of charge

TCF = Temperature correction factor (º C)

φ = Latitude angle

ηb = Battery efficiency (%)

ηINV = Inverter efficiency (%)

ηpv = Efficiency of PV module (%)

ηout = Battery efficiency × inverter efficiency (%)

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Appendices

Appendix - A Table A.1. PV modules specifications and costs Type Nominal

voltage (V)

Shortcut current

(A)

Nominal power (Wp)

Acquisition cost (€)

Maintenance cost per year

(€/year)

Life span

(years) Panel 0 12 0 0 0 0 25

Panel 1 12 3.17 50 387 0 25

Panel 2 12 4.80 80 564 0 25

Panel 3 12 7.54 125 892 0 25

Appendix - B Table B.1. Batteries specifications and costs Type Nominal

capacity (Ah)

Voltage (V)

Acquisition cost (€)

Maintenance cost per year

(€/year)

Float life

(years) Battery 0 0 12 0 0 50

Battery 1 43 12 155 0 12

Battery 2 96 12 258 0 12

Battery 3 200 12 555 0 12

Battery 4 462 12 1017 0 12

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Appendix - C

Table C.1. Inverter specifications and costs

Type Power (VA) Lifetime (year) Acquisition cost (€)

Inverter 0 0 50 0

Inverter 1 3300 10 3608

Inverter 2 4500 10 4138

Inverter 3 10000 10 16048

Inverter 4 13500 10 17786

Appendix – D

Table D.1. Generator specifications and costs

Name Rated power (kVA)

Acquisition cost (€)

Maintenance cost per year

(€/year)

Life span

(hour)

P. min (% of Pn)

Fuel type

Gen 0 0 0 0 100000 30 Diesel

Gen 1 1.9 1269 0.2 7000 30 Diesel

Gen 2 3.0 1514 0.2 7000 30 Diesel

Gen 3 5.5 2314 0.2 7000 30 Diesel

Gen 4 13.5 7200 0.2 7000 30 Diesel

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Appendix – E

Table E. 1. Monthly Average daily solar insolation

Horizontal Surface

Month Irradiation

(kWh/m2) Month

Irradiation

(kWh/m2)

January 4.5 July 4

February 5 August 4.2

March 5.8 September 4.1

April 6.0 October 4.6

May 5.2 November 4.5

June 4.2 December 4.2

LXXXV

REFERENCES

Adhikary, R. B. (1999). Status of Solar PV and Thermal Technology in Nepal,

Practice and Prospects of Income Generating Activities Through Solar

Photovoltaics. 2nd International Seminar on Renewable Energy for

Poverty Alleviation, at IEB, Dhaka, Bangladesh, Nov., 266-27, 1999.

Agustin et. al. (2005). Design of isolated hybrid systems minimizing energy

costs and pollutant emissions. Renewable Energy, 31(14): 2227-2244.

Ashok S. 21. (2006). Optimised model for community-based hybrid energy

system. Renewable Energy 32 (2007) 1155-1164.

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