1

A

PROJECT REPORT

ON

MODELING OF GRID-CONNECTED PHOTOVOLTAIC ENERGY

CONVERSION SYSTEM USED AS A DISPERSED GENERATOR

Submitted in partial fulfillment of the

Requirement for the award of the degree of

MASTER OF TECHNOLOGY

in

ALTERNATE HYDRO ENERGY SYSTEMS

By

ZAMEER AHMAD

ALTERNATE HYDRO ENERGY CENTRE

INDIAN INSTITUTE OF TECHNOLOGY ROORKEE

ROORKEE- 247667 (INDIA)

SEPTEMBER, 2012

2

CANDIDATES DECLARATION

I hereby declare that the work which is presented in this Project, entitled, Modeling

of Grid-connected Photovoltaic Energy Conversion System used as a Dispersed

Generator, submitted in partial fulfillment of the requirement for the award of the degree of

Master of Technology in Alternate Hydro Energy Systems in Alternate Hydro Energy

Centre, Indian Institute of Technology Roorkee, is an authentic record of my own work

carried out during the period from July 2012 to September 2012 under the supervision and

guidance of Shri S.N SINGH, Senior Scientific Officer , Alternate Hydro Energy Centre,

Indian Institute of Technology Roorkee (India).

I also declare that I have not submitted the matter embodied in this dissertation for

award of any other degree.

Date: 27th

SEPT, 2012

Place: Roorkee (ZAMEER AHMAD)

CERTIFICATE

This is to certify that the above statement made by the candidate is

correct to the best of my knowledge.

(S.N SINGH)

Senior Scientific Officer,

Alternate Hydro Energy Centre,

Indian Institute of Technology,

Roorkee 247677.

3

ACKNOWLEDGEMENT

I feel much honored in presenting this Project report in such an authenticable form of

sheer endurance and continual efforts of inspiring excellence from various coordinating

factor of cooperation and sincere efforts drawn from all sources of knowledge. I express my

sincere gratitude to Shri. S.N SINGH Senior Scientific Officer, Alternate Hydro Energy

Centre, Indian Institute of Technology Roorkee for their valuable guidance and infilling

support for the completion of the Project work.

Last but not the least I am also grateful to all faculty members and staff of Alternate

Hydro Energy Centre, Indian Institute of Technology Roorkee.

I extend my thanks to all classmates who have given their full cooperation and

valuable suggestion for my Project work.

Date: 27th

September, 2012

Place: Roorkee (ZAMEER AHMAD)

4

ABSTRACT

The grid integration of renewable energy sources applications based on photovoltaic

systems is becoming today the most important application of PV systems, gaining interest

over traditional stand-alone systems, but grid connection brings problems of voltage

fluctuation and harmonic distortion and reactive power compensation.

A Matlab-Simulink based simulation study of PV module/PV array is carried out and

presented in this work. The simulation model makes use of basic circuit equations of PV solar

cell based on its behavior as diode and comprehensive behavioral study is performed under

varying conditions of solar insolation, temperature, varying diode model parameters, series

and shunt resistance etc. The study is helpful in outlining the principle and intricacies of PV

cell/modules and may be used to verify the impact of different topologies and control

techniques on the performance of different types of PV systems.

The model presented is a generalized structure so that it can be used as a PV power

generator along with wind, fuel cells and small hydro system by establishing proper

interfacing and controllers. The model is simulated connecting a three phase inverter showing

that, the generated dc voltage can be converted to ac and interfaced to ac loads as well as ac

utility grid system

CONTENTS

5

SR.NO. PARTICULARS PAGE NO.

CANDIDATES DECLARATION AND CERTIFICATE i

ACKNOWLEDGEMENT ii

ABSTRACT iii

CONTENTS iv-v

LIST OF FIGURES vi

LIST OF TABLES vii

CHAPTER- 1 INTRODUCTION 1-9

1.1 GENERAL 1

1.2 BRIEF HISTORY OF EXPLOITING SOLAR ENERGY 2

1.3 GLOBAL ENERGY SCENERIO 3

1.4 SOLAR POWER IN INDIA 4

1.5 GOVERNMENT SUPPORT 6

1.5.1 External Support 7

1.6 SOLAR POWER ADVANTAGES 7

1.7 CONCEPT OF DISPERSED GENERATOR 8

1.7.1 The General Definition 8

1.7.2 The Benefits 8

1.7.3 Difficulties 9

CHAPTER-2 MATHEMATICAL MODELING OF PHOTOVOLTAIC

MODULE/ARRAY 10-12

2.1 MODELING OF PHOTOVOLTAIC MODULE/ARRAY 10

2.1.1 PV Cell under varying Insolation 11

2.1.2 PV Cell under Varying Temperature 11

CHAPTER-3 MATLAB SIMULINK MODEL 13-19

3.1 BLOCK DIAGRAM MODEL OF SOLAR PV MODULE/ARRAY IN

MATLAB/SIMULINK 13

3.2 MODEL FOR MAXIMUM POWER POINT TRACKING 17

3.3 MODEL FOR GRID-CONNECTED SOLAR PHOTOVOLTAIC ENERGY

CONVERSION SYSTEM 18

CHAPTER-4 SIMULATION RESULTS 20-30

4.1 SIMULATION OF SOLAR PV MODULE IN MATLAB/SIMULINK 20

6

4.2 PV MODULE CHARACTERISTICS 20

4.2.1 V-I Characteristics 20

4.2.2 Power Curve 21

4.3 MODEL PARAMETER VARIATION 21

4.3.1 Variation in Rs 22

4.3.2 Variation in Rsh 22

4.4 ENVIRONMENTAL PARAMETER VARIATION 23

4.4.1 PV Module under Reduced Insolation 23

4.4.2 PV Module under Varying Temperature 25

4.5 PV ARRAY CHARACTERISTICS 26

CHAPTER-5 CONCLUSION 31

REFERENCES 32-33

7

LIST OF FIGURES

FIGURE NO. PARTICULARS PAGE NO.

1.1 Evolution of global cumulative installed capacity 2000-2011 (MW) 3

1.2 Solar Industry Growth has produced Steadily Falling Prices 4

1.3 India Solar Resource 5

1.4 Solar Market in India 6

2.1 Equivalent circuit of a PV cell 10

3.1 Block Diagram Model of Solar PV Module/Array in Matlab/Simulink 13

3.2 Subsystem of Model of Solar PV Module/Array 13

3.3 Block Diagram Model of photon generated current Iph 14

3.4 Iph Matlab/SIMULINK Subsystem 14

3.5 Block Diagram Model of saturation current Is 15

3.6 Subsystem of Block Diagram Model of saturation current Is 15

3.7 Block Diagram Model of reverse saturation current Irs 16

3.8 Subsystem of Block Diagram Model of reverse saturation current Irs 16

3.9 Maximum power point tracking of PV array by IncCond algorithm 17

3.10 Simulink block diagram for solar photovoltaic energy conversion system 18

3.11 Matlab Simulink block diagram for grid-connected solar photovoltaic 19

4.1 V-I characteristics of PV module 20

4.2 power curve for different insolation 21

4.3 V-I characteristics of a PV cell for three different values of N 21

4.4 PV characteristics with varying Rs 22

4.5 V-I characteristics & power-curves with varying Rsh 23

4.6 PV Module Characteristics with Varying Insolation 24

4.7 PV Module Power Curve For Varying Insolation 24

4.8 PV Module Characteristics with Varying Insolation 24

4.9 Effect of Temperature Variation on PV Module Output 25

4.10 Effect of Temperature variation on power curve 25

4.11 PV Array Characteristics and Power Curves for Varying Insolation 26

4.12 Array power-curves and dP/dV curves for varying insolation 27

4.13 Vmpp and Pmax 27

8

4.14 Vdc, line to line voltage of inverter and Vab load 28

4.15 Three phase inverter output voltage and infinite bus voltage 29

4.16 Three phase current at the output of inverter and infinite bus 30

4.17 DC output current and voltage of SPV 30

LIST OF TABLES

TABLE NO. PARTICULARS PAGE NO.

2.1 Factor N Dependence on PV Technology 11

4.1 Parameters of BP SX150S Solar Module 20

9

CHAPTER-1

INTRODUCTION

1.1 GENERAL

India is endowed with vast solar energy potential. About 5,000 trillion kWh per year

energy is incident over Indias land area with most parts receiving 4-7 kWh per sq. m per

day. Hence both technology routes for conversion of solar radiation into heat and electricity,

namely, solar thermal and solar photovoltaic, can effectively be harnessed providing huge

scalability for solar in India. Solar also provides the ability to generate power on a distributed

basis and enables rapid capacity addition with short lead times. Off-grid decentralized and

low-temperature applications will be advantageous from a rural electrification perspective

and meeting other energy needs for power and heating and cooling in both rural and urban

areas. From an energy security perspective, solar is the most secure of all sources, since it is

abundantly available. Theoretically, a small fraction of the total incident solar energy (if

captured effectively) can meet the entire countrys power requirements. It is also clear that

given the large proportion of poor and energy un-served population in the country, every

effort needs to be made to exploit the relatively abundant sources of energy available to the

country. While, today, domestic coal based power generation is the cheapest electricity

source, future scenarios suggest that this could well change [1].

The world constraint of fossil fuels reserves and the ever rising environmental

pollution have impelled strongly during last decades the development of renewable energy

sources (RES). The need of having available sustainable energy systems for replacing

gradually conventional ones demands the improvement of structures of energy supply based

mostly on clean and renewable resources. At present, photovoltaic (PV) generation is

assuming increased importance as a RES application because of distinctive advantages such

as simplicity of allocation, high dependability, absence of fuel cost, low maintenance and

lack of noise and wear due to the absence of moving parts. Furthermore, the solar energy

characterizes a clean, pollution free and inexhaustible energy source. In addition to these

factors are the declining cost and prices of solar modules, an increasing efficiency of solar

10

cells, manufacturing-technology improvements and economies of scale [2]. The grid

integration of RES applications based on photovoltaic systems is becoming today the most

important application of PV systems, gaining interest over traditional stand-alone systems.

This trend is being increased because of the many benefits of using RES in distributed (aka

dispersed, embedded or decentralized) generation (DG) power systems. These advantages

include the favourable incentives in many countries that impact straightforwardly on the

commercial acceptance of grid-connected PV systems. This condition imposes the necessity

of having good quality designing tools and a way to accurately predict the dynamic

performance of three-phase grid-connected PV systems under different operating conditions

in order to make a sound decision on whether or not to incorporate this technology into the

electric utility grid. This implies not only to identify the currentvoltage (IV) characteristics

of PV modules or arrays but also the dynamic performance of the power conditioning system

(PCS) required to convert the energy produced into useful electricity and to provide

requirements for power grid interconnection.[3],[4]

1.2 BRIEF HISTORY OF EXPLOITING SOLAR ENERGY

In the modern context, solar energy history can be traced to Horace-Benedict de

Sassure, a Swiss scientist who built the first solar oven in 1767. While quite rudimentary in

design, it was nevertheless very successful in application and paved the way for a generation

of technologies and devices that employed solar energy directly. The promise of solar energy

was apparent to everyone by the 19th century. It was an abundant, inexhaustible source of

power. By the 1860s, when oil was still not much in use, it was believed that all coal reserves

would soon run out. Consequently, the world turned to the sun to meet its energy needs.

However, this enthusiasm for solar energy soon faded away as large coal reserves were soon

discovered. Oil and coal, being cheaper to transport and exploit, were preferred over solar

energy, paving the way for much of our modern day environmental problems [5].

In 2010, the photovoltaic industry production more than doubled and reached a world-

wide production volume of 23.5 GWp of photovoltaic modules. Yearly growth rates over the

last decade were in average more than 40%, which makes photovoltaic one of the fastest

growing industries at present. Business analysts predict that investments in PV technology

could double from 35-40 billion in 2010 to over 70 billion in 2015, while prices for

consumers are continuously decreasing at the same time [6]. Evolution of global cumulative

installed capacity 2000-2011 (MW) is shown in figure 1.1.

11

Figure 1.1: Evolution of global cumulative installed capacity 2000-2011 (MW) [7]

1.3 GLOBAL ENERGY SCENERIO

In 2010 world-wide new investments into the renewable energy and energy efficiency

sectors increased to a new record of $ 243 billion, up 30% from 2009 and for the third year in

a row solar power attracted, behind wind, the second largest amount of new investments into

renewable energies[Wor 2011]. Europe was still the leading region in terms of renewable

energy investments, totalling $ 94.4 billion, followed by Asia/Oceania with $ 82.8 billion and

the Americas with $ 65.8 billion [Pew 2011] [6].figure 1.2 shows Solar Industry Growth has

produced Steadily Falling Prices.

Years

MW

12

Figure 1.2: Solar Industry Growth has produced Steadily Falling Prices [8]

1.4 SOLAR POWER IN INDIA

The amount of solar energy produced in India in 2007 was less than 1% of the total

energy demand. The grid-interactive solar power as of December 2010 was merely

10 MW. Government-funded solar energy in India only accounted for approximately

6.4 MW-yr of power as of 2005. However, India is ranked number one in terms of solar

energy production per watt installed, with an insolation of 1,700 to 1,900 kilowatt hours per

kilowatt peak (kWh/KWp). 25.1 MW was added in 2010 and 468.3 MW in 2011. By May

2012 the installed grid connected photovoltaics had increased to over 979 MW, Indias

(Jawaharlal Nehru) National Solar Mission (JJNSM) was launched in January 2010 in order

to achieve the governments target of generating 22 GW (20 GW on-grid; 2 GW off-grid) of

solar power by 2022[9].Figure 1.3 shows India Solar Resource

13

Figure 1.3: India Solar Resource [10]

14

Figure 1.4: Solar Markets in India [11]

1.5 GOVERNMENT SUPPORT

51 Solar Radiation Resource Assessment stations have been installed across India by

the Ministry of New and Renewable Energy (MNRE) to monitor the availability of solar

energy. Data is collected and reported to the Centre for Wind Energy Technology (C-WET),

in order to create a Solar Atlas. The government of India is promoting the use of solar energy

through various strategies. In the latest budget for 2010/11, the government has announced an

allocation of 10 billion (US$199.5 million) towards the Jawaharlal Nehru National Solar

Mission and the establishment of a clean energy fund. It is an increase of 3.8 billion

(US$75.8 million) from the previous budget. This new budget has also encouraged private

solar companies by reducing customs duty on solar panels by 5% and exempting excise duty

on solar photovoltaic panels. This is expected to reduce the cost of a roof-top solar panel

installation by 1520%. The budget also proposed a coal tax of US$1 per metric ton on

domestic and imported coal used for power generation. Additionally, the government has

initiated a Renewable Energy Certificate (REC) scheme, which is designed to drive

investment in low-carbon energy projects.

15

The Ministry of New and Renewable Energy provides 70 percent subsidy on the

installation cost of a solar photovoltaic power plant in North-East states and 30 percentage

subsidy on other regions. The detailed outlay of the National Solar Mission highlights various

targets set by the government to increase solar energy in the country's energy portfolio.

The Mysore City Corporation has decided to set up a mega solar power plant in Mysore with

50% concession from the Government of India. The Maharashtra State Power Generation

Company (Mahagenco) has made plans for setting up more power plants in the state to take

up total generation up to 200 MW.

1.5.1 External Support:

A four-year $7.6 million effort was launched in April 2003 to help accelerate the

market for financing solar home systems in southern India. The project is a partnership

between UNEP Energy Branch, UNEP Risoe Centre (URC), (http://uneprisoe.org/) two of

Indias major banking groups Canara Bank and Syndicate Bank, and their sponsored

Grameen Banks. As per the existing policy, Foreign Direct Investment up to 100 percent is

permitted in non-conventional energy sector through the automatic route. The FDI received

in non-conventional energy sector from January 2003 to September 2006 is estimated at

around Rs.35 crore. The Multilateral Development Banks like World Bank and Asian

Development Bank are also helping India to achieve its potential on renewable resources

[12].

1.6 SOLAR POWER ADVANTAGES

a. It is one of the most environment friendly, clean and safe energy resources.

b. It produces no noise, harmful emissions or polluting gases

c. PV systems are very safe and highly reliable

d. It has lowest gestation period

e Equipment erection and commissioning involve only a few month.

f. It requires low maintenance

g. It can be aesthetically integrated in buildings (BI PV).

h. It contributes to improving the security of energy supply

I. The technological advancements in solar energy systems have made them extremely cost

effective.

16

1.7 CONCEPT OF DISPERSED GENERATOR

In the literature, a large number of terms and definitions are used in relation to

distributed generation. In regards to the rating of distributed generation power units, the

following different definitions are currently used:

1. The Electric Power Research Institute defines distributed generation as generation from a

few kilowatts up to 50 MW [13];

2. According to the Gas Research Institute, distributed generation is typically [between] 25

and 25 MW [14];

3. Preston and Rastler define the size as ranging from a few kilowatts to over 100 MW [15];

4. Cardell defines distributed generation as generation between 500 kW and 1 MW [16];

The International Conference on Large High Voltage Electric Systems (CIGRE) defines DG

as smaller than 50 100 MW [17]

1.7.1 The General Definition

1. Distributed generation is an electric power source connected directly to the distribution

network or on the customer site of the meter.

2. Distributed generation as a small source of electric power generation or storage (typically

ranging from less than a kW to tens of MW) that is not a part of a large central power system

and is located close to the load. [18]

1.7.2 The Benefits [19]

a. Flexibility in price response.

b. Flexibility in reliability needs.

c. Flexibility in power quality needs.

d. Environmental friendliness

e. Substitute for grid investments.

17

1.7.3 Difficulties

The question of power quality and distributed generation is not straightforward. On

one hand, distributed generation contributes to the improvement of power quality. In the

areas where voltage support is difficult, distributed generation offers significant benefits for

the voltage profile and power factor corrections. On the other hand, large-scale introduction

of decentralized power generating units may lead to instability of the voltage profile. The bi-

directional power flows and the complex reactive power management can be problematic and

lead to voltage profile fluctuation. Additionally, short-circuits and overloads are supplied by

multiple sources, each independently not detecting the anomaly [20].

18

CHAPTER-2

MATHEMATICAL MODELING OF PHOTOVOLTAIC

MODULE/ARRAY

2.1 MODELING OF PHOTOVOLTAIC MODULE/ARRAY

The building block of the PV array is the solar cell, which is basically a p-n

semiconductor junction that directly converts solar radiation into dc current using the

photovoltaic effect. Fig.2.1 depicts the well-known equivalent circuit of the solar cell

composed of a light generated current source, a diode representing the nonlinear impedance

of the p-n junction, and series and parallel intrinsic resistances.

Fig.2.1: Equivalent circuit of a PV cell

A mathematical description of current - voltage terminal characteristics for PV cells is

available in literature. The single exponential equation (2.1) which models a PV cell is

derived from the physics of the PN junction and is generally accepted as reflecting the

characteristic behaviour of the cell.

INPIPHNPISexp {q(V/NS+IRS)/(NPKTCN)}-1]-(NPV/NS+IRS)/RSH (2.1)

Iph is the short circuit current

Is is the reverse saturation current of diode (A),

q is the electron charge (1.60210 -19 C),

V is the voltage across the diode (V),

K is the Boltzmanns constant (1.38110 -23 J/K),

T is the junction temperature in Kelvin (K).

N Ideality factor of the diode

Rs is the series resistance of diode,

Rsh is the shunt resistance of diode,

19

The complete behaviour of PV cells are described by five model parameters (Iph, N,

Is, Rs, Rsh) which is representative of the physical behaviour of PV cell/module. These five

parameters of PV cell/module are in fact related to two environmental conditions of solar

insolation & temperature. The determination of these model parameters is not straightforward

owing to non-linear nature of equation (2.1).

2.1.1 PV Cell under varying Insolation

The photon generated current Iph is in fact related with solar insolation S as

IPH= [ISC+KI (TC-Tref)] S/1000 (2.2)

KI = 0.0017 A/C is cells short-circuit current temperature coefficient, ISC is cells

short circuit current at 25 C, T is the cells temperature and S is the solar insolation in

kW/m2. From equation (2.2), it can be seen that at constant temperature, the photon generated

current Iph is directly proportional to solar insolation.

2.1.2 PV Cell under Varying Temperature

The effect of varying temperature on PV cell output is twofold: (i) It affects short

circuit current Isc of Cell as given by equation (2.2). (ii) It changes saturation current of the

diode in PV cell approximately as cubic power and is given by equation (2.3),

IS=IRS (TC/Tref) 3

exp [qEG (1/Tref-1/TC)/KN] (2.3)

Where IRS is the cells reverse saturation current at a reference temperature and a

solar radiation EG is the band-gap energy of the semiconductor used in the cell. The ideal

factor N is dependent on PV technology [21] and is listed in Table2.1.

Table 2.1: Factor N Dependence on PV Technology.

Technology N

Si Mono 1.2

Si Poly 13

a Si:H 18

a Si:H tandem 3.3

a Si:H triple 5

CdTe 1.5

20

All of the model parameters can be determined by examining the manufacturers

specifications of PV products. The most important parameters widely used for describing the

cell electrical performance is the open-circuit voltage VOC and the short-circuit current ISC.

The aforementioned equations are implicit and nonlinear; therefore, it is difficult to arrive at

an analytical solution for a set of model parameters at a specific temperature and irradiance.

Since normally IPH >> IS and ignoring the small diode and ground-leakage currents under

zero-terminal voltage, the short-circuit current ISC is approximately equal to the photocurrent

IPH, i.e.

IPH=ISC (2.4)

On the other hand, the VOC parameter is obtained by assuming the output current is

zero. Given the PV open-circuit voltage VOC at reference temperature and ignoring the shunt

leakage current, the reverse saturation current at reference temperature can be approximately

obtained as

IRS=ISC/ [exp (qvOC/KNNSTC)-1] (2.5)

21

CHAPTER-3

MATLAB SIMULINK MODEL

3.1 BLOCK DIAGRAM MODEL OF SOLAR PV MODULE/ARRAY IN

MATLAB/SIMULINK

The characteristic equations (2.1), (2.2), (2.3) & (2.5) for the PV module is

implemented in MATLAB/Simulink shown in Fig.3.1. and its subsystem is shown in Fig.3.2.

Fig.3.1: Block Diagram Model of Solar PV Module/Array in Matlab/Simulink

Fig.3.2: Subsystem of Model of Solar PV Module/Array

22

The photon generated current Iph is related with solar insolation S as given in

equation (2.2).

The Block Diagram Model of photon generated current Iph is shown in Fig.3.3. and its

subsystem is shown in Fig.3.4.

Fig.3.3: Block Diagram Model of photon generated current Iph

Fig.3.4: Iph Matlab/SIMULINK subsystem for varying cell temperature and solar radiation.

23

Block Diagram Model of equation (2.3) is shown in Fig.3.5. and its subsystem is shown in

Fig.3.6.

Fig.3.5: Block Diagram Model of saturation current Is

Fig.3.6: subsystem of Block Diagram Model of saturation current Is

24

Block Diagram Model of equation (2.5) is shown in Fig.3.7.

Fig.3.7: Block Diagram Model of reverse saturation current Irs

The reverse saturation current subsystem shown in Fig.3.8. is constructed based on equation

(2.5).

Fig.3.8: Subsystem of Block Diagram Model of reverse saturation current Irs

25

3.2 MODEL FOR MAXIMUM POWER POINT TRACKING

The Block diagram used to obtain the power-curves and dP/dV curves for

varying insolation is shown in Fig.3.9.

Fig.3.9: Maximum power point tracking of PV array by IncCond algorithm

26

3.3 MODEL FOR GRID-CONNECTED SOLAR PHOTOVOLTAIC ENERGY

CONVERSION SYSTEM

Matlab Simulink block diagram for solar photovoltaic energy conversion system

supplying power to three phase load is shown in Fig.3.10.

Fig.3.10: Matlab Simulink block diagram for solar photovoltaic energy conversion system

The block diagram comprises of following components:

1. solar photovoltaic array (SPVA)

2. DC filter

3. IGBT based inverter

4. Three Phase

27

Matlab Simulink Block Diagram Model For Grid-Connected Solar Photovoltaic

Energy Conversion System used as dispersed generator is shown in Fig.3.11.

Fig.311: Matlab Simulink block diagram for grid-connected solar photovoltaic energy

conversion system

The block diagram comprises of following components:

1. solar photovoltaic array (SPVA)

2. DC filter

3. IGBT based inverter

4. AC filter

5. Step Up Transformer

6. Three Phase Pi Section Line

7. Three Phase Load

8. Infinite Bus Bar

28

CHAPTER-4

SIMULATION RESULTS

4.1 SIMULATION OF SOLAR PV MODULE IN MATLAB/SIMULINK

The parameters chosen for modeling corresponds to the BP SX150S module as listed

in Table 4.1. The voltage V is considered varying from 0 to open circuit voltage Voc

corresponding to the variation in current from short circuit current Isc to 0.

Table 4.1: Parameters of BP SX150S Solar Module

parameter Value

Maximum power (Pmax) 150W

Voltage at Pmax (Vmax) 34.5V

Current at Pmax (Imax) 4.35A

Short circuit current (Isc) 140A

Open circuit voltage (Voc) 43.5v

Maximum system voltage 600 V

Temp co-efficient of Isc -(0.065+-0.0015)%/c

Temp co-efficient of Voc -(160+-20)mv/c

Temp co-efficient of Power -(0.5+-0.05)%/c

Normal operating cell temp(NOCT) 47+2 C

4.2 PV MODULE CHARACTERISTICS

4.2.1 V-I Characteristics

V-I characteristics of solar module obtained by simulation is shown in Fig.4.1.

Fig.4.1: V-I characteristics of PV module

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6V-I Characteristics for different insolation

Voltage(volts)

Curr

ent(

Am

ps)

1000w/sqm

700w/sqm

400w/sqm

100w/sqm

800w/sqm

29

4.2.2 Power Curve

Power Curve is shown in Fig.4.2.

Fig.4.2:power curve for different insolation

4.3 MODEL PARAMETER VARIATION

The effect of Diode Parameter (N) Variation on open circuit voltage is shown in Fig.4.3.

Fig.4.3: V-I characteristics of a PV cell for three different values of N

Fig.4.3.shows V-I characteristics of a PV module for three different values of N

corresponding to 1, 1.5 & 2 respectively. The ideal value of Ideality -factor N is unity but

its practical value for Silicon PV cell lies between 1 & 2. It can be observed that as we

increase value of N, the open circuit voltage of module increases.

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180P-V Characteristics for different insolation

Voltage (Volts)

Pow

er

(Watt

)

1000W/sqm

800W/sqm

600W/sqm

400W/sqm

100W/sqm

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 450

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

Effect of variation of N

on open circuit voltage of PV

Voltage(V)

Curr

ent(

A)

N=2

N=1.5

N=1

30

4.3.1 Variation in Rs

The PV cell model of Figure 3.1(chapter-3) has two loss representative element Rs

and Rsh. The effect of increasing value of Rs can be seen using simulink model produced for

equation (2.1). The simulation is produced for three different values of Rs as 0.001, 0.01,

and 0.1. The resultant V-I characteristics and power-curves is obtained as shown in Fig.4.4.

The series resistance (Rs) of the PV module has a large impact on the slope of the I-V curve

near the open-circuit voltage (Voc), as shown in the graph. One can observe decay of PV cell

constant current characteristics at an early cell voltage for higher value of Rs, indicating more

output power loss.

Fig.4.4.PV characteristics with varying Rs

The power curves demonstrate that higher value of Rs reduces power output of a cell.

An indicative index known as Fill factor in PV terminology is defined for judgment of

efficient cell operation as given by (2.2):

FF=Pmax/VOC.ISC (6)

The fill factor appreciably gets low for higher value of Rs.

4.3.2 Variation in Rsh

The simulation is produced for three different values of Rsh; 1k, 100 & 10. The

resultant V-I characteristics & power-curves plotted is shown in Fig.4.5. It is observed that

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6PV characteristics with varying Rs

Voltage(v)

Curr

ent(

A)

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180

Pow

er(

W)

V-I Characteristics

Power Curves

0.01 ohm

0.1 ohm

0.001 ohm

31

the smallest value of Rsh causes PV cell current to fall more steeply indicating higher power

loss and low Fill Factor.

All practical PV cell therefore must have high value of Rsh and low value of Rs for

giving more output power and higher Fill Factor.

Fig.4.5. V-I characteristics & power-curves with varying Rsh

4.4 ENVIRONMENTAL PARAMETER VARIATION

4.4.1 PV Module under Reduced Insolation

The two environmental conditions of Solar Insolation and Temperature govern output

of a PV Cell. Simulink is used to demonstrate behaviour of PV cell under varying solar

insolation. it can be seen that at constant temperature, the photon generated current Iph is

directly proportional to solar insolation. If now the rated Isc of specimen PV cell is 4A

under STC (solar insolation of 1 sun at 25C), i.e. 1000 W/m2 insolation.

The effect of varying solar insolation on V-I characteristics can now be produced

using Simulink where the main variable is control voltage V and other variable is insolation.

The simulation is produced for five different values of solar insolation. The resultant V-I

characteristics and power- curves is shown in Fig.4.6.and Fig.4.7.combined curve is shown in

Fig.4.8.

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

Voltage(V)

Curr

ent(

A)

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180PV characteristics with varying Rsh

pow

er(

W)

1ohm

1000 ohm

P-V curve

V-I curve

10ohm

100 ohm

32

Fig.4.6: PV Module Characteristics with Varying Insolation

Fig.4.7: PV Module Power Curve For Varying Insolation

Fig.4.8: PV Module Characteristics with Varying Insolation

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6V-I Characteristics for different insolation

Voltage(volts)

Cu

rre

nt(

Am

ps

)

1000w/sqm

700w/sqm

400w/sqm

100w/sqm

800w/sqm

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180P-V Characteristics for different insolation

Voltage (Volts)

Pow

er

(Watt

)

1000W/sqm

800W/sqm

600W/sqm

400W/sqm

100W/sqm

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6V-I Characteristics and Power Curves of PV Module

Curr

ent(

A)

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180

Voltage(V)

Pow

er(

W)

Power

Curves1000W/sqm

700W/sqm

400W/sqm

100W/sqm

33

From the simulation result it can be observed that as solar radiation falling on PV cell

is reduced, both Isc and Voc decreases, but the change in Voc is not as prominent with

incident solar radiation as is with Isc, which varies almost directly proportional.

4.4.2 PV Module under Varying Temperature

To study the effect of Temperature variation on PV cell output, temperature is taken

as one of the variable in addition to the voltage. V-I characteristics and power curves are

obtained as shown in Fig.4.9.and Fig.4.10.

Fig.4.9: Effect of Temperature Variation on PV Module Output

Fig.4.10: Effect of Temperature variation on power curve

0 5 10 15 20 25 30 35 40 45 50 55 600

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6V-I Characteristics for different temperature

Voltage(Volts)

Curr

ent(

A)

25degC

35degC

45degC

60degC

65degC

70degC

100degC

0 5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

120

140

160

180P-V Characteristics for different temperature

Voltage(V)

Pow

er(

W)

25degC

35degC

45degC

60degC

65degC

70degC

100degC

34

Obviously from equation (2.4) the saturation current of diode of PV cell is highly

temperature dependent and it increases with increase in temperature and is taken care by

Simulink diode model. The increased saturation current in fact reduces open circuit voltage.

4.5 PV ARRAY CHARACTERISTICS

PV array can be simulated in a similar manner by making a slight change in the

equation and simulink model by putting Np = 7 and Ns = 722. The simulated graph is

shown in Fig.4.11.

Fig.4.11: PV Array Characteristics and Power Curves for Varying Insolation

0 10 20 30 40 50 60 70 80 90 1000

5

10

15

20

25

30

PV array characteristics and power curves for varying insolation

Voltage(V)

Cu

rre

nt(

A)

0 10 20 30 40 50 60 70 80 90 1000

400

800

1200

1600

2000

po

we

r(W

)

V-I Chracteristics Power Curves

35

A plot of dP/dV is shown in Figure 4.12. The intersection of the dP/dV graph on

voltage axis i.e. X-Axis gives the voltage corresponding to peak or maximum power of the

PV module (since at voltage axis, the dP/dV=0). The Value of dP/dV is negative on the right

side of the MPP and positive on the left side. Fig.4.13.showing the voltage at which

maximum power occurs.

Fig.4.12: Array power-curves and dP/dV curves for varying insolation

Fig.4.13: Vmpp and Pmax

0 5 10 15 20 25 30 35 40 45 500

5

10

15

20

25

30

35

40Array power-curves and dP/dV curves for varying insolation

dP

/dV

0 5 10 15 20 25 30 35 40 45 500

100

200

300

400

500

600

700

800

900

1000

1100

1200

Voltage(V)

Pow

er(

W)

dP/dV Curves1000W/sqm

700W/sqm

400W/sqm

Power Curves

0 5 10 15 20 25 30 35 40 45 500

5

10

15

20

25

30

35

Voltage

dP

/dV

0 5 10 15 20 25 30 35 40 45 500

100

200

300

400

500

600

700

800

900

1000

1100

1200Maximum power point tracking of PV array by IncCond

pow

er

Pmax

Vmpp

36

Simulation result for solar photovoltaic energy conversion system block diagram

shown in Fig.3.10. (chapter-3) is shown below. The Fig.4.14. shows the following output

signals:

1. Vdc

2. Vab inverter

3. Vab load

Fig.4.14: Vdc, line to line voltage of inverter and Vab load.

The model shown in Fig.3.10. is a generalized structure so that it can be used as a PV

power generator along with wind, fuel cells and small hydro system by establishing proper

interfacing and controllers. The model is simulated connecting a three phase inverter showing

that, the generated dc voltage can be converted to ac and interfaced to ac loads as well as ac

utility grid system. Therefore the model proposed here can be considered as a part of

distributed power generation systems.

37

The simulation result for solar photovoltaic energy conversion system connected to

grid block diagram shown in Fig.3.11 gives the following output signals:

1.Vabc_SPV

2. Vabc_IB (infinite bus)

3. Iabc_IB

4. Iabc_ SPV

5. Vpv_SPV

6. IPV_SPV are shown in Fig.4.15. Fig.4.16and Fig.4.17.

Fig.4.15: Three phase inverter output voltage and infinite bus voltage.

38

Fig.4.16: Three phase current at the output of inverter and infinite bus.

Fig.4.17: DC output current and voltage of SPV.

39

CHAPTER-5

CONCLUSION

A Matlab/SIMULINK model for the solar PV modules and array is developed. This

model is based on the fundamental circuit equations of a solar PV cell taking into account the

effects of physical and environmental parameters such as the solar radiation and cell

temperature. The module model is simulated using Parameters of BP SX150S Solar Module

As a result of the study, one can benefit from this model as a photovoltaic generator in

the framework of the Sim- Power-System Matlab/SIMULINK toolbox in the field of solar

PV power conversion systems. In addition, such a model would provide a tool to predict the

behaviour of any solar PV cell, module and array under climate and physical parameters

changes.

I-V and P-V simulation results show a good agreement in terms of short circuit

current, open circuit voltage and maximum power.

In this study, the Matlab/SIMULINK model not only helps to predict the behaviour of

any PV cell under different physical and environmental conditions, also it can be considered

a smart tool to extract the internal parameters of any solar PV cell including the ideal factor,

series and shunt resistance. Some of these parameters are not always provided by the

manufactures.

The model shown in Fig.3.10.(Chapter-3) is a generalized structure so that it can be

used as a PV power generator along with wind, fuel cells and small hydro system by

establishing proper interfacing and controllers. The model is simulated connecting a three

phase inverter showing that, the generated dc voltage can be converted to ac and interfaced to

ac loads as well as ac utility grid system. Therefore the model proposed here can be

considered as a part of distributed power generation systems.

40

REFERENCES

[1]. http://www.mnre.gov.in/schemes/grid-connected/solar/,19th july,2012

[2]. J. M. Carrasco, L. G. Franquelo, J. T. Bialasiewicz, E. Galvn, R. C. Portillo-Guisa

M. A. Martn-Prats, J. I. Len, N. Moreno-Alfonso, Power electronic systems for

the grid integration of renewable energy sources: a survey, IEEE Trans. Industrial

Electronics, vol. 53, no. 4, pp.1002-1016, 2006.

[3]. W. El-Khattam, M. M. A. Salama, Distributed generation technologies: definitions

and benefits, Electric Power Systems Research, vol. 71, pp. 119-128, 2004.

[4]. A. Poullikkas, Implementation of distributed generation technologies in isolated

power, Renewable and Sustainable Energy Reviews, vol. 11, pp. 30-56, 2007.

[5]. http://www.discover-renewables.com/solar-energy-history.html ,20th july,2012

[6]. PV Status Report 2011, July 2011.

[7]. http://files.epia.org/files/Global-Market-Outlook-2016.pdf

[8]. http://www.intellectualtakeout.org/library/chart-graph/solar-industry-growth-has-

produced-steadily-falling-prices,20th

July,2012

[9]. Global Market outlook For Photovoltaic 2016, May 2012.

[10]. Energy Statistics 2011 (Eighteenth Issue), Central Statistics Office Ministry of

Statistics and Programme Implementation Government of India New Delhi.

[11]. Indian solar energy market outlook 2012, Sept,2010

[12]. http://www.ecoworld.com/products/electronics/indias-solar-power.html,20th July,

2012.

[13]. Gas Research Institute, Distributed Power Generation: A Strategy for a Competitive

Energy Industry, Gas Research Institute, Chicago, USA 1998.

[14]. D. Sharma, R. Bartels, Distributed electricity generation in competitive energy

markets a case study in Australia, in: The Energy Journal Special issue: Distributed

Resources: Toward a New Paradigm of the Electricity Business, The International

Association for Energy Economics, Clevland, Ohio, USA, 1998,pp. 1740.

[15]. J. Cardell, R. Tabors, Operation and control in a competitive market: distributed

Generation in a restructured industry, In the Energy Journal Special Issue:

Distributed Resources: Toward a New Paradigm of the Electricity Business, The

41

International Association for Energy Economics, Clevland, Ohio, USA, 1998, pp.

111135.

[16]. CIGRE, Impact of increasing contribution of dispersed generation on the power

system; CIGRE Study Committee no 37, Final Report, September 1998.

[17]. Distributed generation: a definition, Thomas Ackermann, Goran Andersson ,and

Lennart Soder Department of Electric Power Engineering, Royal Institute of

Technology, Electric Power Systems, Teknikringen 33, 10044 Stockholm, Sweden

Electric Power Systems Group, Swiss Federal Institute of Technology, ETL 626, 8092

Zurich, Switzerland Received 29 June 2000; accepted 05 December 2000

[18]. Juan Manuel Carrasco, Leopoldo Garcia Franquelo, Jan T. Bialasiewicz, Eduardo

Galvn, Ramn C. Portillo Guisado, Ma. ngeles Martn Prats, Jos Ignacio Len and

Narciso Moreno-Alfonso, Power Electronic Systems for the Grid Integration of

Renewable Energy Sources: A Survey IEEE TRANSACTIONS ON INDUSTRIAL

ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006.

[19]. Athimulam Kalirasu, Subharensu Sekar Dash, Simulation of Closed Loop

Controlled Boost Converter for Solar Installation, SERBIAN JOURNAL OF

ELECTRICAL ENGINEERING Vol. 7, No. 1, May 2010, 121-130.

[20]. Thomas Ackermann, Goran Andersson, Lennart Sodera Distributed generation: a

Definition, Electric Power Systems Research 57 (2001) 195204.