mppt report

i

COMPARISON STUDY OF MAXIMUM POWER

POINT TRACKER TECHNIQUES FOR PV SYSTEM

APPLIED TO UNIVERSAL MOTOR

A PROJECT REPORT

Submitted by

DHARMIGARI SHRI SURYA (312211105027)

DUVVURI VENKATA PAVAN KUMAR (312211105030)

KURAPATI VINUTHNA (312211105053)

in partial fulfillment for the award of the degree

of

BACHELOR OF ENGINEERING

in

ELECTRICAL AND ELECTRONICS ENGINEERING

SRI SIVASUBRAMANIYA NADAR COLLEGE OF ENGINEERING,

KALAVAKKAM

ANNA UNIVERSITY: CHENNAI 600025

APRIL 2015

ii

ANNA UNIVERSITY:CHENNAI 600025

BONAFIDE CERTIFICATE

Certified that this project report COMPARISON STUDY OF MAXIMUM

POWER POINT TRACKER TECHNIQUES FOR PV SYSTEM

APPLIED TO UNIVERSAL MOTOR is the bonafide work of

DHARMIGARI SHRI SURYA(312211105027),

DUVVURI VENKATA PAVAN KUMAR (312211105030),

KURAPATI VINUTHNA(312211105053), who carried out the project work

under my supervision.

DR. V.KAMARAJ Mr. M. PANDI KUMAR

HEAD OF THE DEPARTMENT GUIDE

Professor Assistant Professor

Department of Electrical Department of Electrical

andElectronics Engineering andElectronics Engineering

SSN College of Engineering, SSN College of Engineering,

Kalavakkam, Kalavakkam,

Chennai 603110 Chennai - 603110

iii

VIVA VOICE EXAMINATION

The Viva examination for the project work, Comparison study of Maximum

Power Point Tracker techniques for PV system applied to universal motor

submitted by

DHARMIGARI SHRI SURYA(312211105027),

DUVVURI VENKATA PAVAN KUMAR (312211105030),

KURAPATI VINUTHNA(312211105053)

held on ___________________

Internal Examiner External Examiner

iv

ACKNOWLEDGEMENT

I would like to express my gratitude to the below mentioned people who

have been instrumental in the completion of this project.

I express my deep respect to PADMA BHUSHAN Dr. SHIV NADAR,

Chairman, SSN Institutions for working on a great mission and vision and

providing excellent infrastructure.

I thank our President Ms. KALA VIJAYAKUMAR for providing the

required facilities and infrastructure which helped me to complete the project.

The Principal, Dr. S. SALIVAHANAN provided a great support to work. I

express my gratitude to him.

I would like to dedicate my sincere thanks to my guide Dr.

V.KAMARAJ Professor and Head, Department of Electrical and Electronics

Engineering, who has been kind, patient and provided great support. I express

my deep felt gratitude to him.

I would also like to thank our project coordinator Mr.M.PANDI

KUMAR, Assistant Professor, Department of Electrical and Electronics

Engineering, who showed their benevolence and helped us through tough

periods.

I extend my sincere thanks to the staff members and lab technicians,

Department of Electrical and Electronics Engineering for providing great

support at different times. I am grateful to them.

v

ABSTRACT

The need for renewable energy sources is on the rise because of the acute energy

crisis in the world today. India plans to produce 20 Gigawatts Solar power by

the year 2020, whereas we have only realized less than half a Gigawatt of our

potential as of March 2010. Solar energy is a vital untapped resource in a

tropical country like ours. Photovoltaic(PV) offers an environmentally friendly

source of electricity, which is however still relatively costly today. The main

hindrance for the penetration and reach of solar PV systems is their low

efficiency and high capital cost. The maximum power point tracking (MPPT) of

the PV output for all sunshine conditions is a key to keep the output power per

unit cost low for successful PV applications. In order for photovoltaic (PV)

systems to maximize their efficiency of power generation, it is crucial to locate

the maximum power point (MPP) in real time under realistic illumination

conditions. The current-voltage (I-V) characteristics of PV devices are

nonlinear, and the MPP may vary with intrinsic and environmental conditions.

Maximum power point tracking (MPPT) control is expected to seek the MPP

regardless of the device and ambient changes.These techniques vary in many

aspects as simplicity, digital or analogical implementation, sensor required,

convergence speed, range of effectiveness, implementation hardware,

popularity, cost and in other aspects. Our project aims on a comparitive study

between four most popular MPPT techniques which are Incremental

conductance algorithm, Perturb and Observe algorithm , Current sweep method,

vi

Short Circuit Current method and Open Circuit Voltage Method. Universal

motor will be used as load to the PV system. The prototyping PV system is

implemented with a boost DC-DC converter using Microcontroller and

MATLAB Simulink tools to execute the MPPT algorithms. Few comparisons

such as voltage, current and power output for each different combination have

been recorded. The above mentioned algorithms are implemented and tested

under different conditions and the test results are analyzed and compared. This

comparison helps in determining the optimal efficient technique and

significantly improves the tracking accuracy and speed of the MPPT control.

vii

TABLE OF CONTENTS

CHAPTER NO. TITLE PAGE NO.

ABSTRACT iv

LIST OF TABLES ix

LIST OF FIGURES ix

1. INTRODUCTION 1

1.1 NEED FOR RENEWABLE ENERGY

1.2 DIFFERENT SOURCES OF RENEWABLE

ENERGY

1.2.1 WIND POWER

1.2.2 SMALL HYDRO POWER

1.2.3 BIOMASS

1.2.4 GEOTHERMAL

1.2.5 SOLAR POWER

1.3 LITERATURE REVIEW

1.4 OBJECTIVE

1.5 FUTURE SCOPE OF RENEWABLE

ENERGY RESOURCES

1.6 THESIS OUTLINE

2. MODELLING OF PV PANEL 10

2.1 PHOTOVOLTAIC CELL

2.2 PV CELL

2.3 PV ARRAY

2.4 PV MODELLING

2.4.1 NOMENCLATURE

2.4.2 INTRODUCTION

2.4.3 MATHEMATICAL MODEL OF

PHOTOVOLTAIC CELL

viii

2.4.4 REFERENCE MODEL

2.4.5 STEP BY STEP PROCEDURE FOR

SIMULINK MODELLING OF PV

MODULE

2.4.6 CONCLUSIONS

3. BOOST CONVERTER 28

3.1 MODE1 OPERATION OF BOOST

CONVERTER

3.2 MODE2 OPERATION OF BOOST

CONVERTER

3.3 MODELLING OF BOOST CONVERTER

USING MATLAB

3.4 DESIGN APPROACH OF PROPOSED

BOOST CONVERTER

4. MAXIMUM POWERPOINT TRACKING 33

4.1 AN OVERVIEW OF MAXIMUM POWER

POINT TRACKING

4.2 DIFFERENT MPPT TECHNIQUES

4.3 PERTURB AND OBSERVE

4.4 INCREMENTAL CONDUCTANCE

4.5 FRACTIONAL OPEN CIRCUIT VOLTAGE

4.6 FRACTIONAL SHORT CIRCUIT CURRENT

4.7 DETAILS OF PERTURB AND OBSERVE

ALGORITHM

4.7.1 MODELLING OF P&O ALGORITHM

4.7.2 COMPLETE MODEL OF PV PANEL

WITH MPPT

4.7.3 OUTPUT CHARACTERISTICS

4.8 DETAILS OF INCREMENTAL CONDUCTANCE

ALGORITHM

4.8.1 MODELLING OF INCREMENTAL

CONDUCTANCE ALGORITHM


WITH MPPT

ix


4.9 DETAILS OF SHORT CIRCUIT CURRENT

ALGORITHM


WITH MPPT


4.10 DETAILS OF OPEN CIRCUIT VOLTAGE

ALGORITHM


WITH MPPT


4.11 COMPARISON OF MPPT

5. HARDWARE IMPLEMENTATION 45

5.1 HARDWARE COMPONENTS

5.2 HARDWARE SETUP

5.3 SUB CIRCUITS

5.3.1 SUPPLY CIRCUIT

5.3.2 CONTROL CIRCUIT

5.3.3 OPTOCOUPLER CIRCUIT

5.3.4 POWER CIRCUIT

5.4 MATLAB INTERFACE WITH ARDUINO

FOR SERIAL COMMUNICATION

5.5 TESTING AND RESULT

6 CONCLUSION AND FUTURE WORK 51

7 REFERENCES 52

LIST OF TABLES

TABLE NO. TABLE NAME PAGENO.

2.1 ELECTRICAL CHARACTERISTICS 12

DATA OF SOLAR 36W PV MODULE

x

3.1 SPECIFICATIONS FOR BOOST 21

CONVERTER

4.1 COMPARISON OF MPPT ALGORITHM 43

5.1 HARDWARE COMPONENTS 45

LIST OF FIGURES

FIGURE NO. FIGURE NAME PAGENO.

1.1 MPPT TECHNIQUE WITH SOLAR CELL 9

2.1 DIFFERENT SOLAR MODULES 11

2.2 SCHEMATIC CROSS-SECTION OF A TYPICAL 11

SOLAR CELL

2.3 EQUIVALENT CIRCUIT OF PV CELL 12

2 SUBSYSTEM1

3 CIRCUIT UNDER SUBSYSTEM1

4 SUBSYSTEM2


6 SUBSYSTEM3


8 SUBSYSTEM4


10 SUBSYSTEM5


12 SUBSYSTEM6


14 INTERCONNECTION OF ALL 6

SUBSYSTEMS

15 SIMULINK MODELOF PV MODULE

16(a) INPUT TIME VARYING IRRADIATION

16(b) INPUT CONSTANT TEMPERATURE-25 C

16(c) OUTPUT I-V CHARACTERISTICS WITH

VARYING IRRADIATION

16(d) OUTPUT P-V CHARACTERISTICS

WITH VARYING IRRADIATION

17(a) INPUT TIME VARYING TEMPERATURE

17(b) OUTPUT I-V CHARACTERISTICS WITH

xi

VARYING TEMPERATURE

17(c) OUTPUT P-V CHARACTERISTICS

WITH VARYING TEMPERATURE

17(d) OUTPUT POWER VS TIME

3.1 CIRCUIT DIAGRAM OF A BOOST

CONVERTER 29

3.2 MODE 1 OPERATION OF THE BOOST

CONVERTER 29

3.3 MODE 2 OPERATION OF THE BOOST

CONVERTER 30

3.4 MODELLING OF Boost DC-DC

CONVERTER 30

4.1 FLOWCHART OF PERTURB & OBSERVE

ALGORITHM 37

4.2 MODELLING OF P&O ALGORITHM

4.3 COMPLETE MODEL OF PV PANEL WITH

MPPT 37

4.4 OUTPUT CHARACTERISTICS 37

4.5 IINCREMENTAL CONDUCTANCE MPPT

FLOW CHART 38

4.6 MODELLING OF INCREMENTAL

CONDUCTANCE ALGORITHM 38

4.7 COMPLETE MODEL OF PV PANEL

WITH MPPT 38


4.9 FLOWCHART FOR SHORT CICUIT

CURRENT ALGORITHM 40


MPPT 40


4.12 FLOWCHART FOR OPEN CIRCUIT

VOLTAGE ALGORITHM 41


MPPT 41

xii


5.1 HARDWARE SETUP 45

5.1.1 WITHOUT BOOST CONVERTER 46

5.1.2 WITH BOOST CONVERTER

OPERATING 46

5.1.3 BOOST CONVERTER 46

5.1.4 GATE DRIVE CIRCUIT 47

5.1.5 ARDUINO 47

1

CHAPTER 1

INTRODUCTION

It's certainly clear that fossil fuels are mangling the climate and that the status

quo is unsustainable. There is now a broad scientific consensus that the world

needs to reduce greenhouse gas emissions more than 25 percent by 2020 -- and

more than 80 percent by 2050. The idea of harnessing the suns power has been

around for ages.

The basic process is simple. Solar collectors concentrate the sunlight that falls

on them and convert it to energy. Solar power is a feasible way to supplement

power in cities. In rural areas, where the cost of running power lines increases.

Solar power, a clean renewable resource with zero emission, has got tremendous

potential of energy which can be harnessed using a variety of devices. With

recent developments, solar energy systems are easily available for industrial and

domestic use with the added advantage of minimum maintenance. Solar energy

could be made financially viable with government tax incentives and rebates.

An exclusive solar generation system of capacity 250KWh per month would

cost around Rs. 20 lakhs, with present pricing and taxes (2013). Most of the

developed countries are switching over to solar energy as one of the prime

renewable energy source.

1.1 THE NEED FOR RENEWABLE ENERGY

Renewable energy is the energy which comes from natural resources such as

sunlight, wind, rain, tides and geothermal heat. These resources are renewable

and can be naturally replenished. Therefore, for all practical purposes, these

resources can be considered to be inexhaustible, unlike dwindling conventional

fossil fuels. The global energy crunch has provided a renewed impetus to the

2

growth and development of Clean and Renewable Energy sources. Clean

Development Mechanisms (CDMs) are being adopted by organizations all

across the globe. Apart from the rapidly decreasing reserves of fossil fuels in the

world, another major factor working against fossil fuels is the pollution

associated with their combustion. Contrastingly, renewable energy sources are k

known to be much cleaner and produce energy without the harmful effects of

pollution unlike their conventional counterparts.

3

1.2 DIFFERENT SOURCES OF RENEWABLE ENERGY

1.2.1 WIND POWER

Wind turbines can be used to harness the energy available in airflows. Current

day turbines range from around 600 kW to 5 MW of rated power. Since the

power output is a function of the cube of the wind speed, it increases rapidly

with an increase in available wind velocity. Recent advancements have led to

aerofoil wind turbines, which are more efficient due to a better aerodynamic

structure.

1.2.2 SMALL HYDROPOWER

Hydropower installations up to 10MW are considered as small hydropower and

counted as renewable energy sources. These involve converting the potential

energy of water stored in dams into usable electrical energy through the use of

water turbines. Run-of-the-river hydroelectricity aims to utilize the kinetic

energy of water without the need of building reservoirs or dams.

1.2.3 BIOMASS

Plants capture the energy of the sun through the process of photosynthesis. On

combustion, these plants release the trapped energy. This way, biomass works as

a natural battery to store the suns energy and yield it on requirement.

1.2.4 GEOTHERMAL

Geothermal energy is the thermal energy which is generated and stored within

4

the layers of the Earth. The gradient thus developed gives rise to a continuous

conduction of heat from the core to the surface of the earth. This gradient can be

utilized to heat water to produce superheated steam and use it to run steam

turbines to generate electricity. The main disadvantage of geothermal energy is

that it is usually limited to regions near tectonic plate boundaries, though recent

advancements have led to the propagation of this technology.

1.2.5 SOLAR POWER

The tapping of solar energy owes its origins to the British astronomer John

Herschel who famously used a solar thermal collector box to cook food during

an expedition to Africa. Solar energy can be utilized in two major ways. Firstly,

the captured heat can be used as solar thermal energy, with applications in space

heating. Another alternative is the conversion of incident solar radiation to

electrical energy, which is the most usable form of energy. This can be achieved

with the help of solar photovoltaic cells or with concentrating solar power

plants.

As the Photovoltaic module exhibits non-linear V-I Characteristics, which are

dependent on solar Insolation and environment factors, the development of an

accurate power electronic circuit oriented model is essential to simulate and

design the photovoltaic integrated system. In this paper, the design of PV

system using simple circuit model with detailed circuit modelling of PV module

using MATLAB/Simulink and the physical equations governing the PV module

is presented.

5

1.3 LITERATURE REVIEW

Studies show that a solar panel converts 21-40% of energy incident on it to

electrical energy. A Maximum Power Point Tracking algorithm is necessary to

increase the efficiency of the solar panel.

There are different techniques for MPPT such as Perturb and Observe (hill

climbing method), Incremental conductance, Fractional Short Circuit Current,

Fractional Open Circuit Voltage, Fuzzy Control, Neural Network Control etc.

Among all the methods Perturb and observe (P&O) and Incremental

conductance are most commonly used because of their simple implementation,

lesser time to track the MPP and several other economic reasons.

Under abruptly changing weather conditions (irradiance level) as MPP changes

continuously, P&O takes it as a change in MPP due to perturbation rather than

that of irradiance and sometimes ends up in calculating wrong MPP. However

this problem gets avoided in Incremental Conductance method as the algorithm

takes two samples of voltage and current to calculate MPP. However, instead of

higher efficiency the complexity of the algorithm is very high compared to the

previous one and hence the cost of implementation increases. So we have to

mitigate with a trade-off between complexity and efficiency.

It is seen that to get maximum efficiency we are getting which type of

converter. We are choosing here boost converter because it provide us more

voltage at output then input. We can also choose buck-boost converter but due

to our simplification and requirement we are selecting boost converter. It is

very simple to implement and has high efficiency both under stationary and

time varying atmospheric conditions.

6

N. Pandiarajan and Ranganath Muth, This paper presents a unique step-by-

step procedure for the simulation of photovoltaic modules with Matlab/

Simulink. One-diode equivalent circuit is employed in order to investigate I-V

and P-V characteristics of a typical 36 W solar module. The proposed model is

designed with a user-friendly icons and a dialog box like Simulink block

libraries [1].

Alpesh P. parekh, Bhavarty N. Vaidya and Chirag T. Patel, In this paper, the

design of PV system using simple circuit model with detailed circuit modelling

of PV module is presented. In this paper, Equivalent circuit of the PV module &

Simulink model for each equation has presented and complete circuit oriented

model has also presented [2].

Pandiarajan N, Ramaprabha R and Ranganath Muthu, Circuit model of

photovoltaic (PV) module is presented in this paper that can be used as a

common platform for the material scientists as well as power electronic circuit

designers to develop the better PV power plant. Detailed modeling procedure

for the circuit model with numerical dimensions is presented using power

system block set of MATLAB/ Simulink. The developed model is integrated

with DC-DC boost converter with closed loop control of maximum power point

tracking (MPPT) algorithm. The simulation results are validated with the

experimental set up [3].

P.Sathya, Dr.R.Natarajan, this paper presents the design and implementation

of high performance closed loop Boost converter for solar powered HBLED

lighting system. The proposed system consists of solar photovoltaic module, a

closed loop boost converter and LED lighting module. The closed loop boost

converter is used to convert a low level dc input voltage from solar PV module

7

to a high level dc voltage required for the load. To regulate the output of the

converter, closed loop voltage feedback technique is used. The feedback voltage

is compared with a reference voltage and a control signal is generated and

amplified. The amplified signal is fed to 555 Timer which in turn generates a

PWM signal which controls the switching of MOSFET. Thus by switching of

MOSFET it would try to keep output as constant. Initially the boost converter,

timer circuit, amplifier circuit and LED light circuits are designed, simulated

and finally implemented in printed circuit board. The simulation studies are

carried out in MULTISIM. The experimental results for solar PV and boost

converter obtained in both software and hardware was presented in this paper

[7].

Vandana Khanna, Bijoy Kishore Das, Dinesh Bisht, A Simulation model for

simulation of a single solar cell and two solar cells in series has been developed

using Simelectronics (Matlab/Simulink) environment and was presented in this

paper. A solar cell block is available in simelectronics, which was used with

many other blocks to plot I-V and P-V characteristics under variations of

parameters considering one parameter variation at a time. The effect of variation

of parameters such as series resistance, Rs, shunt resistance Rsh, diode

parameters: diode saturation current, Is and ideality factor, N, could be seen on

the characteristics of a single solar cell. Effect of two environmental parameters

of temperature and irradiance variations could also be observed from simulated

characteristics. Matlab coding has been done to find the maximum power

output, Pm, and voltage at maximum power output, Vm, of a single solar cell

and two solar cells (in series) under different values of parameters. The Pmand

Vm values are tabulated here in this paper for variation of one parameter at a

time, considering the diode parameters: Is and N, resistances: series and shunt,

temperature and irradiance [5].

8

G. Venkateswarlu and Dr.P.Sangameswar Raju, The study of photovoltaic

systems in an efficient manner requires a precise knowledge of the IV and PV

characteristic curves of photovoltaic modules. A Simulation model for

simulation of a single solar cell and two solar cells in series has been developed

using Sim electronics (Mat lab /Simulink) environment and is presented here in

this paper. A solar cell block is available in simelectronics, which was used with

many other blocks to plot I-V and P-V characteristics under variations of

parameters considering one parameter variation at a time. Effect of two

environmental parameters of temperature and irradiance variations could also be

observed from simulated characteristics [4].

1.4 OBJECTIVE

The basic objective would be to study MPPT and successfully implement the

MPPT algorithms either in code form as well as using the Simulink/Simscape

model. Modelling of the solar cell in Simulink/Simscape and interfacing both

with the MPPT algorithm to obtain the maximum power point operation would

be of prime importance. After simulating our result with the help of

Simulink/Simscape we would like to implement it on hardware using Field

Programmable Gate Array (FPGA).

Fig.1.1 MPPT Technique with Solar Cell

9

1.5 FUTURE SCOPE OF RENEWABLE ENERGY RESOURCES

The current trend across developed economies tips the scale in favour of

Renewable Energy. For the last three years, the continents of North America and

Europe have embraced more renewable power capacity as compared to

conventional power capacity. Renewables accounted for 60% of the newly

installed power capacity in Europe in 2009 and nearly 20% of the annual power

production

1.6 THESIS OUTLINE

This thesis has been broadly divided into 7 chapters. The first one being the

introduction, chapter 2 is on photovoltaic effect and modelling of solar cell with

Matlab Simulink/Simscape and effect of load mismatching. In chapter 3 we will

study about Boost Converter. Chapter 4 is on maximum power point tracking

and study of the various algorithms. Chapter 5 will discuss about FPGA &

Hardware Implementation. Result and conclusion is discussed in chapter 6 & 7.

10

CHAPTER 2

MODELLING OF PV PANEL

2.1 PHOTOVOLTAIC CELL

A photovoltaic cell or photoelectric cell is a semiconductor device that converts

light to electrical energy by photovoltaic effect. If the energy of photon of light

is greater than the band gap then the electron is emitted and the flow of

electrons creates current.

However a photovoltaic cell is different from a photodiode. In a photodiode

light falls on n-channel of the semiconductor junction and gets converted into

current or voltage signal but a photovoltaic cell is always forward biased.

2.2 PV MODULE

Usually a number of PV modules are arranged in series and parallel to meet the

energy requirements. PV modules of different sizes are commercially available

(generally sized from 60W to 170W). For example, a typical small scale

desalination plant requires a few thousand watts of power

2.3 PV ARRAY

A PV array consists of several photovoltaic cells in series and parallel

connections. Series connections are responsible for increasing the voltage of the

module whereas the parallel connection is responsible for increasing the current

in the array.

11

Fig.2.1 Different Solar Modules

2.4 PV MODELLING

Typically a solar cell can be modelled by a current source and an inverted diode

connected in parallel to it. It has its own series and parallel resistance. Series

resistance is due to hindrance in the path of flow of electrons from n to p

junction and parallel resistance is due to the leakage current.

When irradiance hits the surface of solar PV cell, an electrical field is generated

inside the cell. As seen in Fig.3 this process separates positive and negative

charge carriers in an absorbing material (joining p-type and n-type). In the

presence of an electric field, these charges can produce a current that can be

used in an external circuit. This generated current depends on the intensity of

the incident radiation. The higher the level of light intensity, the more electrons

can be unleashed from the surface, the more current is generated.

12

Fig.2.2 Schematic Cross-Section of a Typical Solar Cell

The most important component that affects the accuracy of the simulation is the

PV cell model. Modelling of PV cell involves the estimation of the I-V and P-V

characteristics curves to emulate the real cell under various environmental

conditions. An ideal solar cell is modelled by a current source in parallel with a

diode. However no solar cell is ideal and thereby shunt and series resistances

are added to the model as shown in the Fig.4

Fig.2.3 Equivalent Circuit of PV Cell

The current source Ipv represents the cell photo current, Rsh and Rs are used to

represent the intrinsic series and shunt resistance of the cell respectively.

Usually the value of Rsh is very large and that of Rs is very small, hence they

may be neglected to simplify the analysis.

2.4.1.NOMENCLATURE

Vpv is output voltage of a PV module (V) Ipv is output current of a PV module

(A)

Tr is the reference temperature = 298 K

T is the module operating temperature in Kelvin

Iph is the light generated current in a PV module (A) Io is the PV module

saturation current (A)

A = B is an ideality factor = 1.6

k is Boltzman constant = 1.3805 10-23

J/K q is Electron charge = 1.6 10-19

C

Rs is the series resistance of a PV module

13

ISCr is the PV module short-circuit current at 25 oC and 1000W/m

2 = 2.55A

Ki is the short-circuit current temperature co-efficient at ISCr = 0.0017A / oC

is the PV module illumination (W/m2) = 1000W/m2

Ego is the band gap for silicon = 1.1 Ev

Ns is the number of cells connected in series Np is the number of cells connected

in parallel

2.4.2.INTRODUCTION

Among the renewable energy resources, the energy due to the photovoltaic (PV)

effect can be considered the most essential and prerequisite sustainable resource

because of the ubiquity, abundance, and sustainability of solar radiant energy.

Regardless of the intermittency of sunlight, solar energy is widely available

and is free. Recently, photovoltaic system is recognized to be in the forefront in

renewable electric power generation. It can generate direct current electricity

without environmental impact and contamination when exposed to solar

radiation. Being a semiconductor device, the PV system is static, quiet, free of

moving parts, and has little operation and maintenance costs.

PV module represents the fundamental power conversion unit of a PV

generator system. The output characteristics of a PV module depend on the solar

insolation, the cell temperature and the output voltage of the PV module. Since

PV module has nonlinear characteristics, it is necessary to model it for the

design and simulation of maximum power point tracking (MPPT) for PV

system applications.

Mathematical modeling of PV module is being continuously updated to enable

researcher to have a better understanding of its working. [1]- [6]

In this paper, a step-by-step procedure for simulating PV module with

14

subsystem blocks, with user-friendly icons and dialog in the same way as

Matlab/ Simulink block libraries is developed. Section III presents the PV

module equivalent circuit and equations for Ipv, the output current from the PV

module. The reference model presented in section IV provides data for Solkar

make 36 W PV module for simulation. In section V, the step-by-step modeling

procedure of PV module is presented with simulation results. Finally, brief

conclusions are drawn in Section VI.

2.4.3.MATHEMATICAL MODEL FOR A PHOTOVOLTAIC MODULE

A solar cell is basically a p-n junction fabricated in a thin wafer of

semiconductor. The electromagnetic radiation of solar energy can be directly

converted to electricity through photovoltaic effect. Being exposed to the

sunlight, photons with energy greater then the band-gap energy of the

semiconductor creates some electron-hole pairs proportional to the incident

irradiation.

The current source Iph represents the cell photocurrent. Rsh and Rs are the

intrinsic shunt and series resistances of the cell, respectively. Usually the value

of Rsh is very large and that of Rs is very small, hence they may be neglected to

simplify the analysis.

PV cells are grouped in larger units called PV modules which are further

interconnected in a parallel-series configuration to form PV arrays.

The photovoltaic panel can be modeled mathematically as given in equations

(1)- (4) [3] [5].

Module photo-current:

I ph [I SCr K i (T 298)] * /1000 (1)

Module reverse saturation current - Irs:

15

I rs I SCr /[exp(qVOC / N S kAT ) 1] (2)

The module saturation current I0 varies with the cell

temperature, which is given by

T 3 q * Eg 0 1 1

I

0

I

rs

[ ] exp[ ] (3)

Tr Bk T

r T

2.4.4.REFERENCE MODEL

Solar make 36 W PV module is taken as the reference module for simulation

and the name-plate details are given in Table 1.

TABLE 2.1: ELECTRICAL CHARACTERISTICS DATA OF

SOLAR 36W PV MODULE

Rated Power 37.08 W

Voltage at Maximum power (Vmp) 16.56 V

Current at Maximum power ( Imp) 2.25 A

Open circuit voltage ( VOC) 21.24 V

Short circuit current ( ISCr) 2.55 A

Total number of cells in series (Ns) 36

Total number of cells in parallel (Np) 1

Note: The electrical specifications are under test conditions of irradiance of 1

kW/m2, spectrum of 1.5 air mass and cell temperature of 25

oC.

2.4.5.STEP BY STEP PROCEDURE FOR SIMULINK MODELING OF

PV MODULE

A model of PV module with moderate complexity that includes the temperature

16

independence of the photocurrent source, the saturation current of the diode,

and a series resistance is considered based on the Shockley diode

equation.Being illuminated with radiation of sunlight, PV cell converts part of

the photovoltaic potential directly into electricity with both I-V and P-V output

characteristics.Using the equations given in section III, simulink modeling is

done in the following steps

A. Step 1

Subsystem 1 is shown in Figure 1. This model converts the module operating

temperature given in degrees Celsius to Kelvin.

B. Step 2

Subsystem 2 is shown in Figure 4. This model takes following inputs.

Insolation/ Irradiation (G / 1000) 1 kW/ m2 = 1.

Module operating temperature TaK = 30 to 70oC

Module reference temperature TrK = 25oC.

17

Short circuit current (ISC) at reference temp. = 2.55A

Fig 4.SUBSYSTEM2

This model calculates the short circuit current ( ISC) at given operating

temperature. Figure 5 gives the circuit under subsystem

C. Step 3

Subsystem 3 is shown in Figure 6. This model takes short circuit current ISC at

reference temp. = 2.55A and Module reference temperature TrK = 25oC as

input.

18

Using equation 2, the reverse saturation current of the diode is calculated in

subsystem 3. Figure 7 gives the circuit under subsystem 3.

D. Step 4

Subsystem 4 is shown in Figure 8.

19

This model takes reverse saturation current Irs, Module reference temperature

TrK = 250 C and Module operating temperature TaK as input and calculates

module saturation current. Figure 9 gives the circuit under subsystem 4.

E. Step 5


This model takes operating temperature in Kelvin TaK and calculates the

20

product NsAkT, the denominator of the exponential function in equation (4).

Figure 11 gives the circuit under subsystem 5.

F. Step 6


This model executes the function given by the equation (4). The following

function equation is used.

IPV = u(3)-u(4)*(exp((u(2)*(u(1)+u(6)))/(u(5)))-1)

Figure 13 gives the circuit under subsystem 6.

21

G. Step 7

All above six models are interconnected as given in Figure 14.

Figure 14. Interconnection of all six subsystems

The final model is shown in Figure 15. The workspace is added to measure Ipv,

Vpv, Ppv in this model. The time tout is stored in workspace with scope model

can be used to plot graph.

22

The final model takes irradiation, operating temperature in Celsius and module

voltage as input and gives the output current Ipv and output voltage Vpv.

Matlab code for plotting XY graph is given below.

plot (Vpv,Ipv)

plot (Vpv, Ppv)

The code for plotting scope signals is

plot(tout,Ipv)

H. Performance Estimation

With the developed model, the PV module characteristic is estimated as follows.

(i) I-V and P-V characteristics under varying

irradiation with constant temperature are obtained as shown in Figures 16(a) to

16(d).

1. In Figure 16(a), the input irradiation is shown. Between 0 and 1 s, the

irradiation is 200W/m2, between 1 and 2 s it is 600 W/m, while from 2 s

onwards it is 1000W/m2.

23

4. The P-V output characteristics of PV module with varying irradiation at

24

constant temperature are shown in Figure 16(d).

_ The above graphs are user friendly.

_ When the irradiation increases,

_ The current output increases

_ The voltage output also increases. This results in net increase in power output

with increase in irradiation at constant temperature.

(ii) I-V and P-V Characteristics under constant irradiation with varying

temperature are obtained in Figures 17(a) to 17(d).

1. In Figure 17(a) the time varying temperature signal is shown. Between 0 and

1 second, the temperature of 250C is applied and it is increased to 50 and 750C.

25

2. The I-V output characteristics of PV module with varying temperature at

constant irradiation of 1000W/m2 are shown in Figure 17(b).

3. The P-V output characteristics of PV module with varying temperature at

constant irradiation are shown in Figure 17(c).

4. The output power vs. time of PV module is shown in Figure 17(d). The

power output reduces with increase in temperature at constant irradiation.

26

_ When the operating temperature increases,

_ The current output increases marginally

_ But the voltage output decreases drastically

_ Results in net reduction in power output with rise in temperature

The results are verified and found matching with the manufacturers data sheet

output curves.

2.4.6. CONCLUSIONS

The step-by-step procedure for modeling the PV module is presented.

Thismathematical modeling procedure serves as an aid to induce more people

into photovoltaic research and gain a closer understanding of I-V and P-V

characteristics of PV module.

REFERENCES

[1] M.Veerachary,Power Tracking for Nonlinear PV Sources with Coupled

Inductor SEPIC Converter, IEEE Transactions on Aerospace and Electronic

Systems, vol. 41, No. 3, July 2005.

[2] I. H. Altas and A.M. Sharaf, A Photovoltaic Array Simulation Model for

Matlab-Simulink GUI Environment, IEEE, Clean Electrical Power,

International Conference on Clean Electrical Power (ICCEP '07), June 14-16,

27

2007, Ischia, Italy.

[3] S.Chowdhury, S.P.Chowdhury, G.A.Taylor, and Y.H.Song, Mathematical

Modeling and Performance Evaluation of a Stand-Alone Polycrystalline PV

Plant with MPPT Facility, IEEE Power and Energy Society General Meeting -

Conversion and Delivery of Electrical Energy in the 21st Century, July 20-24,

2008, Pittsburg, USA.

[4] Jee-Hoon Jung, and S. Ahmed, Model Construction of Single Crystalline

Photovoltaic Panels for Real-time Simulation, IEEE Energy Conversion

Congress & Expo, September 12-16, 2010, Atlanta, USA.

[5] S. Nema, R.K.Nema, and G.Agnihotri, Matlab / simulink based study of

photovoltaic cells / modules / array and their experimental verification,

International Journal of Energy and Environment, pp.487- 500, Volume 1, Issue

3, 2010.

28

CHAPTER 3

BOOST CONVERTER

A boost converter is designed to step up a fluctuating or variable input voltage

to a constant output voltage of 24 volts with input range of 6-23volts in. To

produce a constant output voltage feedback loop is used. The output voltage is

compared with a reference voltage and a PWM wave is generated, here Spartan

6 FPGA kit is used to generate PWM signal to control switching action.

A DC to DC converter is used to step up from 12V to 24V. The 12V input

voltage is from the battery storage equipment and the 24V output voltage serves

as the input of the inverter in solar electric system. In designing process, the

switching frequency, f is set at 20 kHz and the duty cycle, D is 50%.

Here we want to introduced an approach to design a boost converter for

photovoltaic (PV) system using microcontroller. The converter is designed to

step up solar panel voltage to a stable 24V output without storage elements such

as battery. It is controlled by a FPGA unit using voltage-feedback technique.

The output of the boost converter is tracked, measured continuously and the

values are sent to the microcontroller unit to produce pulse-width-modulation

(PWM) signal. The PWM signal is used to control the duty cycle of the boost

converter. Typical application of this boost converter is to provide DC power

supply for inverter either for grid-connected or standalone system. Simulation

and experimental results describe the performance of the proposed design.

Spartan 6 FPGA is used to perform tasks in the proposed design.

As stated in the introduction, the maximum power point tracking is basically a

load matching problem. In order to change the input resistance of the panel to

29

match the load resistance (by varying the duty cycle), a DC to DC converter is

required.

It has been studied that the efficiency of the DC to DC converter is maximum

for a buck converter, then for a buck-boost converter and minimum for a boost

converter but as we intend to use our system either for tying to a grid or for a

water pumping system which requires 230 Vat the output end, so we use a boost

converter.

Fig.3.1 Circuit Diagram of a Boost Converter

3.1. MODE 1 OPERATION OF THE BOOST CONVERTER When the switch is closed the inductor gets charged through the battery and

stores the energy.In this mode inductor current rises(exponentially) but for

simplicity we assume that the charging and the discharging of the inductor are

linear.The diode blocks the current flowing and so the load current remains

constant which is being supplied due to the discharging of the capacitor.

Fig.3.2 Mode 1 Operation of the Boost Converter

3.2. MODE 2 OPERATION OF THE BOOST CONVERTER In mode 2 the switch is open and so the diode becomes short circuited. The

energy stored in the inductor gets discharged through opposite polarities which

charge the capacitor. The load current remains constant throughout the

30

operation. The waveform for a boost converter are shown in figure.

Fig.3.3 Mode 2 Operation of the Boost Converter 3.3. MODELING OF BOOST CONVERTER USING MATLAB SIMSACPE

Fig.3.4 Modelling of Boost DC-DC Converter

3.4. DESIGN APPROACH OF PROPOSED BOOST CONVERTER Load Requirement: The load is a simple 4 x 4 LED panel and each row

containing 4 LED in a line would require a current of 10- 15 mA and thus total

of 60 mA to all four branches and thus having a resistance of 570. As each

LED gives a drop of 2.1 volts to become forward biased, so a minimum of 8.4

31

volts is required to glow 4 LED in series, for this a voltage of 24 V is required

to be supplied to LEDs. Thus the load requirement is 570 with 42 mA of total

current thus required voltage was 24 V. Since a potential divider is used whose total resistance is 1100 so total

equivalent resistance is Req = (1100) (570) = 375.Based on this load

requirement the other parameters would be calculated and the specifications are

tabulated in the following table.

Table 3.1 Specification for Boost Converter

S.No. Component Value

1 Inductor 290H 2 MOSFET 1N5408 IRF 840 3 Power Diode IN5408 4 Input Capacitor 470F 5 Output Capacitor 330 F 6 Resistive Load 50, 50W

Duty Cycle: The duty cycle can be found using the following relation-

D=1

Inductor value: The value of inductor is determined using the following relation Lmin=D (1-D

2)*R/2*Fs

An inductor is practically designed using the following parameters and is shown

in the figure 22.

Formula for inductor design, L = (d2n2) / (l + 0.45d)

Required dimensions of inductor Coil length, l= 8.1 cm

Diameter, d= 6.3 cm Inductance value required, L= 151 H Number of turns, n=64

32

Where L is inductance in micro Henrys, d

is coil diameter in meters, l is coil length in meters, and n is

number of turns

Capacitor value: The value of capacitor is determined from the following equation

C=D/Fs*R*Vr Where C is the minimum value of capacitance,

D is duty cycle, R is output resistance, Fs is switching frequency, and Vr is output voltage ripple factor.

33

CHAPTER 4

MAXIMUM POWER POINT TRACKING ALGORITHM

4.1. AN OVERVIEW OF MAXIMUM POWER POINT TRACKING

A typical solar panel converts only 30 to 40 percent of the incident solar

irradiation into electrical energy. Maximum power point tracking technique is

used to improve the efficiency of the solar panel. According to Maximum

Power Transfer theorem, the power output of a circuit is maximum when the

Thevenin impedance of the circuit (source impedance) matches with the load

impedance. Hence our problem of tracking the maximum power point reduces

to an impedance matching problem. In the source side we are using a boost

convertor connected to a solar pan el in order to enhance the output voltage so

that it can be used for different applications like motor load. By changing the

duty cycle of the boost converter appropriately we can match the source

impedance with that of the load impedance.

4.2. DIFFERENT MPPT TECHNIQUES There are different techniques used to track the maximum power point. Few of

the most popular techniques are:

1) Perturb and Observe (hill climbing method)

2) Incremental Conductance method 3) Fractional short circuit current 4) Fractional open circuit voltage

4.3 PERTURB & OBSERVE

Perturb & Observe (P&O) is the simplest method. In this we use only one

sensor, that is the voltage sensor, to sense the PV array voltage and so the cost

34

of implementation is less and hence easy to implement. The time complexity of

this algorithm is very less but on reaching very close to the MPP it doesnt stop

at the MPP and keeps on perturbing on both the directions. When this happens

the algorithm has reached very close to the MPP and we can set an appropriate

error limit or can use a wait function which ends up increasing the time

complexity of the algorithm. However the method does not take account of the

rapid change of irradiation level (due to which MPPT changes) and considers it

as a change in MPP due to perturbation and ends up calculating the wrong MPP.

To avoid this problem we can use incremental conductance method.

4.4. INCREMENTAL CONDUCTANCE

Incremental conductance method uses two voltage and current sensors to sense

the output voltage and current of the PV array. At MPP the slope of the PV

curve is 0.

(dP/dV)MPP=d(VI)/dV

0=I+VdI/dVMPP

dI/dVMPP = - I/V

The left hand side is the instantaneous conductance of the solar panel. When

this instantaneous conductance equals the conductance of the solar then MPP is

reached. Here we are sensing both the voltage and current simultaneously.

Hence the error due to change in irradiance is eliminated. However the

complexity and the cost of implementation increases. As we go down the list of

algorithms the complexity and the cost of implementation goes on increasing

which may be suitable for a highly complicated system. This is the reason that

Perturb and Observe and Incremental Conductance method are the most widely

used algorithms. Owing to its simplicity of implementation we have chosen the

Perturb & Observe algorithm for our study among the two.

35

4.5. FRACTIONAL OPEN CIRCUIT VOLTAGE

The near linear relationship between VMPP and VOC of the PV array, under varying

irradiance and temperature levels, has given rise to the fractional VOC method.

VMPP = k1 Voc where k1 is a constant of proportionality. Since k1 is dependent on the

characteristics of the PV array being used, it usually has to be computed

beforehand by empirically determining VMPP and VOC for the specific PV array at

different irradiance and temperature levels. The factor k1 has been reported to be

between 0.71 and 0.78. Once k1 is known, VMPP can be computed with VOC

measured periodically by momentarily shutting down the power converter.

However, this incurs some disadvantages, including temporary loss of power.

4.6. FRACTIONAL SHORT CIRCUIT CURRENT Fractional ISC results from the fact that, under varying atmospheric conditions, IMPP

is approximately linearly related to the ISC of the PV array.

IMPP =k2 Isc

Where k2 is a proportionality constant. Just like in the fractional VOC technique, k2

has to be determined according to the PV array in use. The constant k2 is generally

found to be between 0.78 and 0.92. Measuring ISC during operation is problematic.

An additional switch usually has to be added to the power converter to periodically

short the PV array so that ISC can be measured using a current sensor.

4.7. DETAILS OF PERTURB & OBSERVE ALGORITHM

The Perturb & Observe algorithm states that when the operating voltage of

the PV panel is perturbed by a small increment,if the resulting change in power P is

positive,then we are going in the dir of perturbationection of MPP and we keep on

36

perturbing in the same direction.If P is negative,we are going away from the

direction of MPP and the sign of perturbation supplied has to be changed.

The flowchart for the P&O algorithm is shown in the figure

Fig.4.1 Flowchart Of Perturb & Observe Algorithm

4.7.1. MODELLING OF P&O ALGORITHM

Fig.4.2 Modelling of P&O Algorithm

37

4.7.2. COMPLETE MODEL OF PV PANEL WITH MPPT

Fig.4.3 Complete Model of PV Panel With MPPT


FIG 4.4 OUTPUT CHARACTERISTICS

38

4.8 DETAILS OF INCREMENTAL CONDUCTANCE ALGORITHM

The flowchart for the Incremental Conductance algorithm is shown in the figure

Fig-4.5:Incremental conductance MPPT Flow chart

39

4.8.1. MODELLING OF INCREMENTAL CONDUCTANCE

ALGORITHM

Fig.4.6 Modelling of Incremental Conductance Algorithm

4.8.2. COMPLETE MODEL OF PV PANEL WITH MPPT


40


PV CELL OUTPUT INC CONDUCTANCE OUTPUT


4.9 DETAILS OF SHORT CIRCUIT CURRENT ALGORITHM

The flowchart for the Short Circuit Current algorithm is shown in the figure

FIG 4.9 FLOWCHART FOR SHORT CICUIT CURRENT ALGORITHM

41

4.9.1. COMPLETE MODEL OF PV PANEL WITH MPPT(SHORT CIRCUIT

CURRENT)



PV CELL OUTPUT SHORT CIRCUIT CURRENT OUTPUT


42

4.9DETAILS OF FRACTIONAL OPEN CIRCUIT VOLTAGE ALGORITHM

The flowchart for the Open Circuit Voltage algorithm is shown in the figure

FIG 4.12 FLOWCHART FOR OPEN CIRCUIT VOLTAGE ALGORITHM

4.9.1. COMPLETE MODEL OF PV PANEL WITH MPPT(OPEN CIRCUIT

VOLTAGE)


43

4.9.2 OUTPUT CHARACTERISTICS:

PV CELL OUTPUT OPEN CIRCUIT VOLTAGE OUTPUT


4.10 COMPARISON OF MPPT ALGORITHMS:

Comparing different parameters, it is evident that each algorithm is suited for

different purposes. Below table shows a comparison between these algorithms.

ERRORS P AND O INCREMENTAL

CONDUCTANCE

SHORT

CIRCUIT

CURRENT

OPEN

CIRCUIT

VOLTAGE

MEAN

ABSOLUTE

PERCENTAGE

ERROR

0.093780528

0.00442

0.098105

0.578062

MEAN

PERCENTAGE

ERROR

9.3780528

0.442

9.8105

57.8

MEAN

ABSOLUTE

ERROR

0.1

0.002264999

0.133459

1.74725082

TABLE 4.1 COMPARISON OF MPPT ALGORITHMS

44

Conclusion from the table 4.1

Due to minimum error in Incremental Conductance,Incremental Conductance is

the Optimum Algorithm.

4.11 COMPLETE MODEL OF PV PANEL WITH MPPT(INCREMENTAL

CONDUCTANCE) APPLIED TO UNIVERSAL MOTOR

45

CHAPTER 5

HARDWARE IMPLEMENTATION

5.1 Hardware Components

The Components used for the project are listed in the Table 5.1

Table 5.1 Hardware Components

COMPONENT NAME SPECIFICATION

Capacitor 470 F ,50 V

Inductor ecore 22 SWG (0.5mH)

Mosfet IRF 840

Diode IN4007 , 3A

Transformer 220/12 V

Optocoupler IC TLP 250

Resistors 460,1k,1.2 k

Universal motor 240v,60Hz,,50-1000W

Adruino

46

5.2 Hardware Setup

The entire Hardware Setup for the project is Shown in the Figure 5.1

Figure 5.1 Hardware SetupFIG 5.1.1 Without Boost Converter

Fig 5.1.2With Boost Converter Operating

47

Fig 5.1.3 BOOST CONVERTER

Fig 5.1.4 Gate Drive Circuit

Fig 5.1.5 Arduino

48

5.3 Sub Circuits

The entire hardware setup consists of the following sub circuits:

1. Supply Circuit

2. Control Circuit

3. Optocoupler Circuit

4. Power Circuit

5.3.1 Supply Circuit

The AC input supply is stepped down to 12 V from 230 V using a step down

transformer. Using a diode bridge rectifier AC voltage is converted to DC voltage.

5.3.2 Control Circuit

The control circuit is used to produce the pulses to trigger the MOSFET of

the boost converter.

5.3.3 Optocoupler Circuit

The optocoupler circuit is used to isolate the Power Circuit from Control

Circuit. The supply of 12 V is given to the pin 5 and the output of the optocoupler

is taken from pin 4 and it is used to trigger the MOSFET switch of the boost

converter.

5.3.4 Power Circuit

The power circuit consists of consists of the boost converter whose

output voltage greater than the input voltage depending on the boost mode of

operation.

49

5.4 Matlab interface with Arduino for serial communication:

MATLAB Support Package for Arduino(also referred as Arduino-I/O

Package) allows us to communicate with an Arduino over a serial port.It

consists of a MATLAB API on the host computer and a server program that

runs on the Arduino.Together,they allow us to access transmit and receive serial

data from Arduino.

In this project we received data from Arduino such as solar current reading (I),

solar voltage reading (V), solar power reading (P), time (in Sec) (T), battery

voltage reading (Vb) and develop a real time plot of I-V, P-V on Matlab to monitor

maximum power point of solar array And also plot graph of V, P, I, Vb

with respect to time to check variation in this parameter.

5.5 TESTING AND RESULT.

The experimental test was recorded in Chennai, India. Perturb & observer and

Incremental conductance algorithms based MPPT experiments are performed on

these days to show the robustness to the varying atmosphere and compare their

performances. We take real time reading on Matlab for 100 second and plot graph

of I vs. V, P vs. V and also plot graph of P, V, I, Vb with respect to time. Results

of perturb & observer method are shown in Fig-10 and Fig-11 in which Fig -10.

has graph of solar power, solar voltage, solar current, battery voltage with respect

to time from which we got instantaneous value of solar voltage, solar current, solar

power with respect to time and in Fig-11 shows the graph of solar current versus

solar voltage and solar power versus solar voltage which shows maximum power

point generated by the solar panels when the solar charger was running the perturb

and observer algorithm in which solar charger charges battery.

50

Similarly the Results of incremental conductance method are shown in Fig -12 and

Fig -13 in which Fig -12 has graph of solar power, solar voltage, solar current,

battery voltage with respect to time from which we would get instantaneous value

of solar voltage, solar current, solar power with respect to

time and in Fig -13 shows the graph of solar current versus solar voltage and solar

power versus solar voltage which shows maximum power point generated by the

solar panels when the solar charger was running the incremental conductance

algorithm in which solar charger charges battery.

Fig -10 and Fig -13 represents graphs of maximum power point tracker when

battery is in bulk condition so it tracks the maximum power point algorithm. Fig -

14 and Fig -15 represents graphs of maximum power point tracker when battery is

in float condition. In this state we try and keep the battery voltage at 14 volt by

decreasing the pwm value.

51

CHAPTER 6

CONCLUSION AND FUTURE WORK

Using MPPT with solar panel installations has clear advantages. The initial

investment is smaller because smaller panel wattage is required (very little

potential power is wasted), and adding correct battery-charging algorithms

will also decrease operating costs (batteries are protected and last longer).

In this project we present four MPPT algorithms implemented on a synchronous

Boost converter and compare them on real time graph obtain in Matlab. From this

we come to know that Incremental conductance method has less oscillation.The

maximum power point tracker works because there is a difference between the

solar panels MPP voltage and the batterys charging voltage. The IV curves for an

actual solar panel show that the MPP voltage goes down as the temperature of the

solar panel goes up, this means that the solar panels Maximum power point

voltage is lower as the panel temperature rises. On the other hand, if the

temperature of the solar panel is low and the battery is mostly discharged, the

maximum power point tracker will show higher power gains. My experience with

maximum Power point Tracking has shown that large power gains are possible

only under ideal circumstances. If the solar panels are cool, the batteries mostly

discharged and voltage drops in the system are low, maximum power point tracker

gets higher efficiency should occur. Under other conditions the maximum power

point tracker efficiency will be lower, especially if the solar panels are being used

in hot conditions

52

REFERENCES:

1.Arun KumarVerma, Bhim Singh and S.C Kaushik, An Isolated Solar Power

Generation using Boost Converter and Boost Inverter, in Proc. National

Conference on Recent Advances in Computational Technique in Electrical

Engineering, SLITE, Longowal (India), 19-20 March, 2010, paper 3011, pp.1-8.

2.Comparison of MPPT Algorithms for DC-DC Converters Based PV Systems by

A.Pradeep Kumar Yadav,S.Thirumaliah,G.Haritha International Journal of

Advanced Research in Electrical, Electronics and Instrumentation Engineering

Vol. 1, Issue 1, July 2012

3.Eftichios Koutroulis and Freder Blaabjerg , (2012), A New Technique

for Tracking the Global Maximum Power Point of PV Arrays Operating

Under Partial-Shading Conditions , IEEE Journal of Photovoltaics , Vol. 2 , No. 2,

pp. 184-190.

4.G. Acciari, D. Graci, and A. La Scala, (2011), Higher PV module efficiency

by a novel CBS bypass, IEEE Trans. Power Electron, Vol. 26, No. 5, pp.

13331336.

5.G. Villalva, J. R. Gazoli, E. Ruppert F, "Modeling and circuit-based simulation

of photovoltaic arrays", Brazilian Journal of Power Electronics, 2009 vol. 14, no.

1, pp. 35-45, ISSN 1414-8862.

53

6.International Conference on Microelectronics, Communication and Renewable

Energy (ICMiCR-2013)

Experimental Implementation of Micro-controller based MPPT for Solar PV

System Ahmed Bin-Halab,Adel Abdennour,Hussein Mashlay in-Halabi Adel

Abdennour Hussein Mashaly Department of Electrical Engineering ,King Saud

University ,Riyadh, Saudi Arabia.

7.Mihnea Rosu-Hamzescu, Sergiu Opera Practical Guide to Implementing

Solar Panel MPPT Algorithms"

8.M. Miyatake, M. Veerachary, F. Toriumi, N. Fujii, and H. Ko, (2011)

Maximum power point tracking of multiple photovoltaic arrays: A PSO

approach, IEEE Trans. Aerosp. Electron. Syst., Vol. 47, No. 1, pp. 367380.

9.M. Berrera, A. Dolara, R. Faranda and S. Leva, Experimental test of seven

widely-adopted MPPT algorithms, 2009 IEEE Bucharest Power Tech Conference,

June 28th - July 2nd, Bucharest, Romania.

10.N.Pandiarajan and Ranganath Muth Mathematical Modeling of

Photovoltaic Module with Simulink in 2011 1st International Conference on

Electrical Energy Systems.

11. N. Femia, G. Petrone, G. Spagnuolo and M. Vitelli, (2005)

Optimization of and observe maximum power point tracking method, IEEE

Trans. Power Electron., Vol. 20, No. 4, pp. 963973.

54

12.Nevzat Onat, Recent Developments inMaximumPower Point Tracking

Technologies for Photovoltaic Systems, Hindawi Publishing Corporation

International Journal of Photoenergy Volume 2010, Article ID 245316, 11 pages.

13.Pandiarajan N, Ramaprabha R and Ranganath Muthu Application Of

Circuit Model For Photovoltaic Energy Conversion System

14.P.Sathya, Dr.R.Natarajan Design and Implementation of 12V/24V Closed

loop Boost Converter for Solar Powered LED Lighting System in International

Journal of Engineering and Technology (IJET) Volumeg No 1 Feb-Mar 2013.

15.P. S. Revankar, W. Z. Gandhare and A. G. Thosar Government College of

Engineering, Aurangabad, Maximum Power Point Tracking for PV Systems

Using MATLAB/SIMULINK, 2010 Second International Conference on Machine

Learning and Computing.

page1page2page3page5page4page27

mppt report

Documents

project work

duvvuri venkata pavan

great support

pv system

pandi kumar head

kamaraj professor

universal motor

project coordinator