Proj Final

[Type the company name]

[Type the document title]

[Type the document subtitle]

sameera

[Pick the date]

[Type the abstract of the document here. The abstract is typically a short summary of the contents of the document. Type the abstract of the document here. The abstract is typically a short summary of the contents of the document.]

List of contents

Ackknoledgement 3

List of symbols

List of figures

Abstract

Chapter.1

Introduction to maximum peak power tracking

Introduction

Need to mppt

How mppt is obtained

Algorithms used

Applications of MPPT

Chapter.2

Litrerature review

Chaper.3

Algorithm used to generate mppt

Perturb and observe

Incremental condutane

Pasitic capacitance

Voltage contolled mpt

current cotroled tracing

chapter.4

introduction to matlab/simulink

chapter.5

simulation on matlab/simulink

chatper.6

results

4

6

7

2

chapter.7

conclutions and futurescope

coclutions

futurescope

chapter.8

references

3

ACKNOWLEDGEMENT

I would like to take this oppurtunity to thank each and every person who made this project possible . I am thankful to OU for giving this opurtunity to work on the project report as a part of the curriculum. I would also like to express my deep gratitude to Ms.Hajira Fathima and Mrs. Aijaz Fathima for their invaluble support and co-operation . the constant support and encoragement had motivated me give my best which can be seen in this report.

4

List of symbols

V Voltage V

Vo Output voltage V.

Vi Input voltage V.

dV Voltage error V.

vd Voltage across diode V.

I Current A.

Iph Photon generated current A.

Id Current through diode A.

IL Load current A.

∆I Current ripple A.

R Resistance Ω.

Ro Output resistance Ω.

Ri Input resistance Ω.

RL Load resistance Ω.

C Capacitance F.

5

L Inductance H.

D Duty cycle ratio.

∆D Change in duty cycle ratio.

G Insolation level W/m2.

P Power W.

dP

t

Power error

dc/dc converter on

W.

switching period ms.

ton On period of converter ms.

toff Off period of converter ms.

k Stefan Boltzman constant.

1.38x10-23

J/K

T Temperature in K.

q Electronic charge C.

f frequency of the

converter kHz.

7

6

L ist o f F i g u r e s

Fig.1.Characteristics of a typical solar PV module.

Fig.2.Changes in the characteristics of the solar pv module due to change in

insolation level

Fig.3.Change in the module characteristics due to the change in temperature

Fig.4.Block diagram of a typical MPPT system

Fig.5.DC/DC converter helps in tracking the peak power point.

Fig.6.Battery charging application of MPPT

Fig.7.Grid connected application using MPPT

Fig.8. Pumping application of the MPPT.

Fig.9. Perturb and observe algorithm

Fig.10.Incremental conductance method.

Fig.11. Solar cell Equivalent Model

Fig.12. Simulink model of the solar PV module.

Fig.13. PV module model.

Fig.14. I-V characteristics of the module.

Fig.15. P-V characteristics of the module.

Fig.16. Perturb and observe algorithm

Fig.17. Step down or Buck converter (Vo<Vi).

Fig.18. Step Up or Boost converter(Vo>Vi).

Fig.19. MPPT system simulink setup.

Fig.20. Implementation of algorithm in simulink.

Fig 21. Initial duty ratio 0.65(right half of the PV curve).

Fig.22. Initial duty ratio equal to unity (left half of the PV curve)

7

ABSTRACT

In todays world reneuable energy sources play a very important rile in electricity genegratioin. For meeting ou rdaily demands we may use wind, solar ,thermal ,geo- thermal, and biomass.

Energy from the sun is the best option for electricity generationas it is available everywhere and is free to harness.on an average the sunshine hour in india is about 6hrs annually also the sun shines in india for about 9 months in a year.electricity from the sun can be generated throuh the solar photovoltaic modules(SPV). The SPV is avialable in various power power output to meet the the load requirements.

Maximization of power from a solar photo voltaic module (SPV) is of special intrest as the efficiency of the PV module is low. A peak power tracker is used for extracting maximum power from from the SPV module.the present work describes a maximum peak power tracker for SPV module connected to a ressistive load. Here we are are carring out simmulation studies in MATLAB /SIMULINK.

8

CHAPTER. 1

INTRODUCTION TO MAXIMUM PEAK POWER POINT TRACKING

(MPPT)

9

1.1 Introduction

Reneuable energy sources play n important role in elctric power generation .various reneuable sources such as solar energy ,wind enrgy, geothermal energy etc. are harnesssed for electric power generation.solar energy is directly converted into electrical energy by photovoltaic module.

The photovoltaic modules are made up of sillicon cells .the sillicon solar cells which give output voltage of around 0.7V under open circuit condition.when connected in series this module which generally consists of 36 solar cells produces an open circuit voltage of upto 20V.the current rating of the module depends on the area of individual cells .i.e. higher the the area of the cell higher is the current output of the cell. For obtaining higher power output the solar PV modules are connected in series and parallel combinations forming solar PV arrays. A typical chareecteristic curve of the current(I) and voltage(V) curve and power(W) and voltage (V) curve of the module are shown in the fig.1

10

1.2 need for maximum power point tracking

power output of a solar pv midule changes in direction of sun, changes in solar insolation level and with varying temparatures as shown in fig.2 and fig.3

As seen in the PV(power vs. voltage )curve of the module there is a single maxima of power .i.e. there exists a single peak power corresponding to a particular votage and current. Now we know that the efficiency is low for a solar module about 13%.since the module efficiency is low it is desirable to operate the module at the peak power point so that the maximium power can be delivered to the load under the varying temperature and insolation conditions. Hence the maximization power improves the utillitilization of the solar PV module. An MPPT is used for extracting the maximum power from thesolar PV module and transferring that power to the load. A dc/dc converter (step up/step down)serves the purpose of transferring maximumpower from the solar PV module to the load. A dc/dc converter acta as an interface between the load and the module fig.4.

11

By changing the duty cycle the load impedence as seen by the source is varied and matched at the pointof the peakpower with the source so as to transfer the maximum power.

12

1.3 How maximum power point is obtained

As discussed earier in the chapter the maximum peak power point is obtained by introducing a dc/dc converter in between the load and solar PV module. The duty cycle of the converter is changed till the peak power point is obtained.

Considerining a step down converter here,

V₀=D*Vі……………………………………………………………………………………………………………...(1)

(V₀ is the output voltage and Vі is the input voltage)

On solving for impedance transfer ratio

R₀= D²*Rі………………………………………………………………………………………………………………(2)

(R₀ is the output impedence and Rі is the input impedence as seen by the source)

Rі=R₀/D²………………………………………………………………………………………………………………..(3)

Thus output resistance R₀ remains constant and by changing the the duty cycle the input resistance Rі seen by the source changes. So the resistance corresponding to the peak power point is obtained by chainging the duty cycle. As shown in the fig.5.

13

1.4 Methods of Peak Power Tracking

The peak power is reached with the help of a dc/dc converter by adjusting the duty cycle such that the resistance corresponding to the peak power is obtained. Now quesyion arises how to vary the duty cycle and in which direction so that it reaches the peak power , wheather manual tracking or automatic tracking? Manual tracking is not possible so automatic tracking is preferred to manual tracking. Automatic tracking can be performed by utillizilling the following algorithms,

a. Perturb and Observeb. Incremental Conductancec. Paracitic Capacitanced. Voltage based Peak Power ackere. Curent based Peak Power Tracker

The algorithms can be implemented either on a microcontroller or a PC to implement maximum power tracking. The algorithm changes the duty cycle of the dc/dc converter to maximizethe power output of the module and make it operate at the peak power point of the module. Various algorithims seed above are explained in the following discussion.

1.5 Applications of Maximum Power Point Tracker

MPPT systems are used mainly in systems where source of power is non-linear such as the solar PVmodules or the wind generator systems. MPPT systems are generally used in solar PV applications such as battery chargers and grid connected stand alone PV systems.

a. Battery charging - charging of battery(lead acid/NiCad)which is used for the storage of electrical energy. This energy if it comes from the solar PV systems then fast charging of the battery can be done with the help of the MPPT charge controller.

b.

PV Module

MPPT System

Battery

c.

d. Fig.6.Battery charging application of MPPT

14

e. Grid connected and standalone PV systems - in grid connected or stand alone PV systems the solar array supplies power to the grid or to the local load. A dc/dc converter is used as the array voltage is dc and as grid voltage is an dc/ac converter must be used. Before a dc/ac converter a dc/dc converter(normally step up)is used which serves the purpose of the maximum power point tracking as explained earlier. Due to maximum power tracking always , the peak power is transferred to the grid or the local load.

f. Water pumping application - solar PV arrays can be used to run dc motor which drive the pumpfor suppling the water in the fields. By using the maximum power point tracker the power of the motor can be increased and so the output flowrate of the pump will also increase.

15

CHAPTER. 2LITRERARY REVIEW

16

The following literature survey for the current report consists of various papers published by IEEE and from journals.

a. Optimization of Perturb and Observe Maximum Power point method .

Nicola femia, Giovanni Petrone , Giovanni Spagnuolo, Massimo Vitteli

Maximum power point tracking (MPPT) techniques are used in photovoltaic(PV)systems to maximize the Pvarray output power by tracking continuosly the maximum power point(MPP)which depends on panel temparature and on irradiance conditions. The issue of MPPT has been adressed in differentways in different litreture but, especially for low-cost implementations,the perturb and observe(P&O) maximum power point tracking algorithm is the most commonly used method due to its easeof implementation. A drawbavk of p&o is that , at steady state,the operating point oscillates around the MPP giving rise to awaste of enrgy ; moreover it is known that the algorithm maybe confused at those time intervals charecterized by rapidly changing atmosphericconditions. Here it is shown that, in orer to limit the negetive effects associated with the above drawbacks, the P&O MPPT parametres must be customised to the dynamic behaviour of the specific converter adopted. A theoritical analysis allowing the optimal choice of such parametres is also carried out.

b. Maximum power tracking for photovoltaic power systems

Joe-Air Jiang, Tsong-Liang Huang, Ying-Tusg Hsiao and Chia-Hong Chen

The electric power supplied by aphotovoltaic power generation system depends on the solar radiation and temperature. Designing efficient PV systems heavily emphasizes to track the maximumpower operating point. This work develps a novel three-point weight comparison method that avoidsthe oscillation problem of the perturbation and observationalgorithm which is often emlployed to track the maximum power point. Furthermore ,a lowcst unit is developed on a single chip to adjust the output voltage of the solar cell array. Finally , experimental results prove superior performanceof the proposed method.

c. An improved photovoltaic power supply system with tracking

J.Devishree ,Dr.Anbalagan, J.Rathinavel, S Sentil

In this paper an otimum design of a multiple carrier pulse width modulation (MPWM)inverter for a grid connected photovoltaic energy conservation system along with DSP-controlled maximum power point tractionusing combined dynamics and static PV array is proposed the MPPT provides much improved tracking operation under different conditions such as changing insolation and temperature. in this single stage PV convertion system is used and multi carrier pulse width modulation technique is used to control the output of the inverter.

17

d. Implementation of a DSP controlled Photovoltaic System with Peak Power Tracking

Chihchiang Hua , Jongrong Lin , and Chihming Shen

The authour discusses an improved MPPt algorithm based on the perturb and observe. The algorithm uses the power as the control variable based on the perturbation and observation method. The algorithm requires two sensors. A better responsefor the system under rapidly varying conditions is obtained by increasing the execution speed. A T1320C25 DSP is used to implement the proposed MPPT controller. The simullation of the MPPT algorithm is carried out and verifiedwith practical results. Modelling of the step down converter used for the peak power tracking is carried out. PI controller design and its response for the the MPPT systemis also discussed. The controller and the MPPT algorithm are implemented through th PC utillizing a DSP processor T132C25of Texas Instruments.

e. Control of dc/dc converters fro solar enrgy system with maxium power tracking

Chichiang hua and chihming shen

The object of this paper is to analyze and design dc/dc convrters of different types in a solar enrgy system to investigate the performance of th converters. A simple method which combines a discrete time control and and PI compensatoris used to track the maximum power points(Mpp’s) of the solar array. The system Is kept to operate close to MPPTS ,thus the maximum possible power transfer from the solar array is achieved. The implementation of the proposed converter system was basedon a digital signal processocesor (DSP). Experimental tests where carried out for buck ,boost and buck-boost coverters using simple MPPT algorithms. The efficienices of different systems are compared. The paper is useful in evauating the responseof step up , step down converter for the MPPT sysstem. Paper proposes that the step down converter is the best option for the use in the MPPT systemas it gives higher efficiency.

18

CHAPTER. 3

Algorithms to Track the Maximum Power Point

19

As explained earlier in chapter 1.4, we will discuss the various algorithms which help in tracking the peak power point of the PV module automatically. The different algorithms are

a. Perturb and Observeb. Incremental Conductancec. Parasitic Capacitanced. Voltage based Peak Power trackere. Current based Peak Power tracker

3.1 Perturb and observe : in this algorithm a slight perturbation is introducedto the system. Due to this perturbation the power of the module changes.if the power increases due to the perturbation then the perturbation is continued in the same direction. After the peak power is reached the power at the next instant decreases and hence after that after that the perturbation reverses.

When a steady state is reached the algorithm oscillates around the peak point. In order to keep the power variation smallthe perturbation size is kept small. The algorithm is developed in such a manner that it sets a reference voltage of the module corresponding to the peak voltage of the module. a PI controller then acts moving the operating point of the module to that particular voltage level. It is observerd that there are some power losses due to this perturbation also the failure to track the power under fast varying atmospheric conditions. But still this algorithm is very popular and simple.

3.2 Increamental conductance : the disadvange of perturb and observe method to tracck the peak power under fast varying atmospheric condition is overcome by Incremental conductance method. The algorithm makes use of the equation

P=V*I……………………………………………………………………………………………………….(4)

(where P=module power,V=module voltage,I=module current)

Diff with resp to dV

dP/dV=I+V*dI/dV………………………………………………………………………………………(5)

depending on this equation the algorithm works,

20

3

at peak point

dP/dV=0……………………………………………………………………………………………………….(6)

dI/dV=I/V………………………………………………………………………………………………………(7)

if the operating point is to the righ of th power curve then we have

dP/dV<0…………………………………………………………………………………………………….(8)

dI/dV<I/V…………………………………………………………………………………………………..(9)

if the operating point is to the left of the curve,

dP/dV>0……………………………………………………………………………………………………..(10)

dI/dV>I/V…………………………………………………………………………………………………….(11)

from equations 7,9,10 the algorithm works.

The incremental conductance can determine that the MPPT has reached the mpp and stop perturbing the operating point. If this condition is not met ,the directiojn in which the the mppt operating point must be perturbed cab be calculatedusing the relationship between dI/dV and - I/V.this relationship is derived from the fact that the dP/dV is negative when the mppt is to the right of the positive when it is left of MPP. The algorithm has advantages over perturb and observe that it can determine when the mpp has been recheahd ,when the perturb and observe oscilates around the mpp. Also incremental conductance can track, rapidly increasing and decresing irradiance conditions with higher accuracy than perturb and observe. One disadvantage of this algorithm is that the increased complexity when compared to perturb and observe.

3.3 parasitic capacitance : the parasitic capacitance method is a refinement of the incremental conductance method that takes into account the pasitic capacitances of the solar cells in the PV array. Parasitic capacitance uses the switching ripple of the MPPT to perturb the array. To account for the parasitic capacitance, the average ripple of the MPPT to perturb the array. To account for the parasitic capacitance,the average ripple in the array power and voltage, generated by the switching frequency,

21

are measured using a series filters and multipliers and it is used to calculate the array conduntance. the incremental conductance alogorithm is then used to determine the direction to move the operating point of the MPPT. One disadvantage of this algorithm is that the parasitic conductance in each module is very small and will come into play only in a large PV arrays where several module strings are connected in parallel. Also , the dc/dc converter has a sizable input capacitorused to filter out small ripple in the array power. This capacitor may mask the overall effect of the parasitic capacitance of the PV array.

3.4 Voltage control maximum point tracker : it is assumed that a maximum power point of a particular solar PV modulelies at about 0.75 timesthe open circuit voltage of the module. So by measuring the open circuit voltage a ref voltage can be genrated and feedforward voltage control a refrence voltage schme can be implemented to bring the solar pv module to the point of maximum power. One problem of this technique is the open ircuit voltage of the module varies with temperature , so as the temperature increases the module open circuit voltage also changes accordingly and we have to measure the oen circuit voltage very often. Hence the load must be disconnected from the module to measure the open circuit voltage. Due to which the power during that instant will not b utilized.

3.5 Curent controlled maximum power point tracking : the peak power power tracker of the module lies at the point which is at about 0.9 times the short circuit current of the module. In order to measure this point the module or array is short circuited and than by using the current mode control the module current is adjusted to the value which is approx 0.9 times the short circuit current. The problem with this method is that a high gain power resistor is required which can be sustain the short circuit current. The module has to be short circuited to measure the short circuit current as it goes on varying with the changes in insolation level.

22

Chapter. 4

Introduction to Matlab®/S imulink®

Overview

23

Simulink® software models, simulates, and analyzes dynamic systems. It enables you to pose a question about a system, model the system, and see what happens. With Simulink, you can easily build models from scratch, or modify existing models to meet your needs. Simulink supports linear and nonlinear systems, modeled in continuous time, sampled time, or a hybrid of the two. Systems can also be multirate — having different parts that are sampled or updated at different rates.Thousands of scientists and engineers around the world use Simulink to model and solve real problems in a variety of industries, including:

Aerospace and Defense Automotive Communications Electronics and Signal Processing Medical Instrumentation

Tool for Model-Based Design

With Simulink, you can move beyond idealized linear models to explore more realistic nonlinear models, factoring in friction, air resistance, gear slippage, hard stops, and the other things that describe real-world phenomena. Simulink turns your computer into a laboratory for modeling and analyzing systems that would not be possible or practical otherwise. Whether you are interested in the behavior of an automotive clutch system, the flutter of an airplane wing, or the effect of the monetary supply on the economy, Simulink provides you with the tools to model and simulate almost any real-world problem. Simulink also provides demos that model a wide variety of real-world phenomena (see Simulink Demo Models).Simulink provides a graphical user interface (GUI) for building models as block diagrams, allowing you to draw models as you would with pencil and paper. Simulink also includes a comprehensive block library of sinks, sources, linear and nonlinear components, and connectors. If these blocks do not meet your needs, however, you can also create your own blocks. The interactive graphical environment simplifies the modeling process, eliminating the need to formulate differential and difference equations in a language or program.Models are hierarchical, so you can build models using both top-down and bottom-up approaches. You can view the system at a high level, then double-click blocks to see increasing levels of model detail. This approach provides insight into how a model is organized and how its parts interact.

Tool for Simulation

After you define a model, you can simulate it, using a choice of mathematical integration methods, either from the Simulink menus or by entering commands in the MATLAB® Command Window. The menus are convenient for interactive work, while the command line is useful for running a batch of simulations (for example, if you are doing Monte Carlo simulations or want to apply a parameter across a range of values). Using scopes and other display blocks, you can see the simulation results while the simulation runs. You can then change many parameters and see what happens for "what if" exploration. The simulation results can be put in the MATLAB workspace for postprocessing and visualization.

24

Tool for Analysis

Model analysis tools include linearization and trimming tools, which can be accessed from the MATLAB command line, plus the many tools in MATLAB and its application toolboxes. Because MATLAB and Simulink are integrated, you can simulate, analyze, and revise your models in either environment at any point.

How Simulink Software Interacts with the MATLAB Environment

Simulink software is tightly integrated with the MATLAB environment. It requires MATLAB to run, depending on it to define and evaluate model and block parameters. Simulink can also utilize many MATLAB features. For example, Simulink can use the MATLAB environment to:

Define model inputs. Store model outputs for analysis and visualization. Perform functions within a model, through integrated calls to MATLAB operators

and functions.Starting Simulink Software

Opening the Simulink Library BrowserYour MATLAB environment must be running before you can open Simulink software. You start Simulink from within MATLAB.To start Simulink and open the Simulink Library Browser:

1. Start MATLAB. For more information, see Starting a MATLAB Session in the MATLAB Getting Started Guide.

2. Enter simulink in the MATLAB Command Window.

The Simulink Library Browser opens.

25

Opening a ModelYou can open existing Simulink models or create new models from the Simulink Library Browser.To create a new model:

Select File > New > Model in the Simulink Library Browser.The software opens an empty model window.

To open an existing model:1. Select File > Open in the Simulink Library Browser.

The Open dialog box appears.2. Select the model (.mdl file) you want to open, then click Open.

The software opens the selected model in the model window.

Simulink User Interface

Simulink Library Browser

The Library Browser displays the Simulink block libraries installed on your system. You build models by copying blocks from a library into a model window.

26

Simulink Library Browser

Tips for Using the Library Browser

When using the Library Browser, note the following: You can view the blocks in a library by selecting the library name on the left side

of the Library Browser, or by double-clicking the library. When you select a block, a description of that block appears at the bottom of the

browser. For more information on a block, select the block, then select Help > Help on the

Selected Block to display the help page for the block. You can view the parameters for a block by right-clicking the block, then

selecting Block Parameters. You can search for a specific block by entering the name of the block in the block

search field, then clicking the Find block icon .

Standard Block Libraries

Simulink software provides 16 standard block libraries. The following table describes each of these libraries.

Block Library Description

Commonly Used Contains a group of the most commonly used blocks, such as the Constant,

27

Block Library Description

Blocks In1, Out1, Scope, and Sum blocks. Each of the blocks in this library are also included in other libraries.

Continuous Contains blocks that model linear functions, such as the Derivative and Integrator blocks.

Discontinuities Contains blocks with outputs that are discontinuous functions of their inputs, such as the Saturation block.

Discrete Contains blocks that represent discrete time functions, such as the Unit Delay block.

Logic and Bit Operations

Contains blocks that perform logic or bit operations, such as the Logical Operator and Relational Operator blocks.

LookUp Tables Contains blocks that use lookup tables to determine their outputs from their inputs, such as the Cosine and Sine blocks.

Math Operations Contains blocks that perform mathematical and logical functions, such as the Gain, Product, and Sum blocks.

Model Verification Contains blocks that enable you to create self-validating models, such as the Check Input Resolution block.

Model-Wide Utilities

Contains blocks that provide information about the model, such as the Model Info block.

Ports & Subsystems

Contains blocks that allow you to create subsystems, such as the In1, Out1, and Subsystem blocks.

Signal Attributes Contains blocks that modify the attributes of signals, such as the Data Type Conversion block.

Signal Routing Contains blocks that route signals from one point in a block diagram to another, such as the Mux and Switch blocks.

Sinks Contains blocks that display or export output, such as the Out1 and Scope blocks.

Sources Contains blocks that generate or import system inputs, such as the

28

Block Library Description

Constant, In1, and Sine Wave blocks.

User-Defined Functions

Contains blocks that allow you to define custom functions, such as the Embedded MATLAB®Function block.

Additional Math & Discrete

Contains two additional libraries for mathematical and discrete function blocks.

Simulink Model Window

The model window contains the block diagram of the model. You build models in the model window by arranging blocks logically, setting the parameters for each block, and then connecting the blocks with signal lines. The model window also allows you to:

Set configuration parameters for the model, including the start and stop time, type of solver to use, and data import/export settings.

Start and stop simulation of the model. Save the model. Print the block diagram.

Getting Help with Simulink softwareSimulink software provides comprehensive online help that describes Simulink features, blocks, and functions, and provides detailed procedures for common tasks. The help includes online versions of all Simulink documentation, including:

Simulink Getting Started Guide (this guide) Simulink User's Guide Simulink Reference Writing S-Functions Simulink Release Notes

You access the online help from the Help menu of the Simulink Library Browser or model window. To access the online help:

From the Simulink Library Browser, select Help > Simulink Help. From the Simulink model window, select Help > Using Simulink.

Simulink Demo ModelsSimulink software provides a variety of demo models that illustrate key modeling concepts and Simulink features. You can access these demos from the MATLAB Command Window.To access Simulink demos:

1. On the bottom left corner of the MATLAB Command Window, click the Start button.The Start menu appears.

2. Select Simulink > Demos from the Start menu.

29

Creating a Simple Model

Creating a New Model

Before you can begin building your model, you must start Simulink and create an empty model.To create a new model:

1. If Simulink is not running, enter simulink in the MATLAB Command Window to open the Simulink Library Browser.

2. Select File > New > Model in the Simulink Library Browser to create a new model.The software opens an empty model window.

Adding Blocks to Your Model

To construct a model, you first copy blocks from the Simulink Library Browser to the model window. To create the simple model in this chapter, you need four blocks:

Sine Wave — To generate an input signal for the model Integrator — To process the input signal Scope — To visualize the signals in the model Mux — To multiplex the input signal and processed signal into a single scope

To add blocks to your model:1. Select the Sources library in the Simulink Library Browser.

The Simulink Library Browser displays the Sources library.2. Select the Sine Wave block in the Simulink Library Browser, then drag it to the

model window.A copy of the Sine Wave block appears in the model window.

3. Select the Sinks library in the Simulink Library Browser.4. Select the Scope block from the Sinks library, then drag it to the model window.

A Scope block appears in the model window.5. Select the Continuous library in the Simulink Library Browser.6. Select the Integrator block from the Continuous library, then drag it to the model

window.An Integrator block appears in the model window.

7. Select the Signal Routing library in the Simulink Library Browser.8. Select the Mux block from the Sinks library, then drag it to the model window.

A Mux block appears in the model window.

Moving Blocks in the Model Window

Before you connect the blocks in your model, you should arrange them logically to make the signal connections as straightforward as possible. To move a block in the model window, you can either:

Drag the block. Select the block, then press the arrow keys on the keyboard.

Arrange the blocks in the model to look like the following figure.

Connecting Blocks in the Model Window

30

After you add blocks to the model window, you must connect them to represent the signal connections within the model. Notice that each block has angle brackets on one or both sides. These angle brackets represent input and output ports:

The > symbol pointing into a block is an input port. The > symbol pointing out of a block is an output port.

The following describe how to connect blocks by drawing lines from output ports to input ports:

Drawing Lines Between Blocks Drawing a Branch Line

Drawing lines between blocksYou connect the blocks in your model by drawing lines between output ports and input ports. To draw a line between two blocks:

1. Position the mouse pointer over the output port on the right side of the Sine Wave block.Note that the pointer changes to a cross hairs (+) shape while over the port.

2. Drag a line from the output port to the top input port of the Mux block.Note that the line is dashed while you hold the mouse button down, and that the pointer changes to a double-lined cross hairs as it approaches the input port of the Mux block.

3. Release the mouse button over the output port.The software connects the blocks with an arrow that indicates the direction of signal flow.

4. Drag a line from the output port of the Integrator block to the bottom input port on the Mux block.The software connects the blocks.

5. Select the Mux block, then Ctrl+click the Scope block.

The model should now look similar to the following figure. Drawing a branch lineThe model is almost complete, but one connection is missing. To finish the model, you must connect the Sine Wave block to the Integrator block. This final connection is somewhat different from the other three, which all connect output ports to input ports. Because the output port of the Sine Wave block already has a connection, you must connect this existing line to the input port of the Integrator block. The new line, called a branch line, carries the same signal that passes from the Sine Wave block to the Mux block.To weld a connection to an existing line:

1. Position the mouse pointer on the line between the Sine Wave and the Mux block. 2. Press and hold the Ctrl key, then drag a line to the Integrator block's input port.

The software draws a line between the starting point and the input port of the Integrator block.

The model is now complete. It should look similar to the following figure.

Saving the Model

After you complete the model, you should save it for future use.To save the model:

31

1. Select File > Save in the model window.2. Specify the location in which you want to save the model.3. Enter simple_model in the File name field.4. Click Save.

The software saves the model with the file name simple_model.mdl.Simulating the ModelAfter you complete the model, you can simulate it and visualize the results. This section describes how to simulate the sample model you created in the previous section.

Setting Simulation OptionsBefore simulating a model, you can set simulation options such as the start and stop time, and the type of solver that Simulink software uses to solve the model at each time step. You specify these options using the Configuration Parameters dialog box. To specify simulation options for the sample model:

1. Select Simulation > Configuration Parameters in the model window.The software displays the Configuration Parameters dialog box. Enter 20 in the Stop time field.

2. Click OK.The software applies your changes to the parameters and closes the Configuration Parameters dialog box.

.

Running the Simulation and Observing ResultsNow you are ready to simulate your example model and observe the simulation results.To run the simulation:

1. Select Simulation > Start in the model window.The software runs the model, stopping when it reaches the stop time specified in the Configuration Parameters dialog box.

2. Double-click the Scope block in the model window.The Scope window displays the simulation results.

3. Select File > Save in the model window.The software saves the model.

4. Select File > Close in the model window.The software closes the model.

3. From the Simulink demos page in the MATLAB Help browser, click the demo model you want to open.

Web Site ResourcesYou can access additional Simulink resources on the MathWorks™ Web site, including Simulink related books, prerecorded webinars, and technical support. To access the Simulink product page, go to:http://www.mathworks.com/products/simulink

Simpowersystems

32

SimPowerSystems software and other products of the Physical Modeling product family work together with Simulink software to model electrical, mechanical, and control systems.SimPowerSystems software operates in the Simulink environment. Therefore, before starting this user's guide, make yourself familiar with Simulink documentation. Or, if you perform signal processing and communications tasks (as opposed to control system design tasks), see the Signal Processing Blockset™ documentation.

The Role of Simulation in Design

Electrical power systems are combinations of electrical circuits and electromechanical devices like motors and generators. Engineers working in this discipline are constantly improving the performance of the systems. Requirements for drastically increased efficiency have forced power system designers to use power electronic devices and sophisticated control system concepts that tax traditional analysis tools and techniques. Further complicating the analyst's role is the fact that the system is often so nonlinear that the only way to understand it is through simulation.Land-based power generation from hydroelectric, steam, or other devices is not the only use of power systems. A common attribute of these systems is their use of power electronics and control systems to achieve their performance objectives.SimPowerSystems software is a modern design tool that allows scientists and engineers to rapidly and easily build models that simulate power systems. It uses the Simulink environment, allowing you to build a model using simple click and drag procedures. Not only can you draw the circuit topology rapidly, but your analysis of the circuit can include its interactions with mechanical, thermal, control, and other disciplines. This is possible because all the electrical parts of the simulation interact with the extensive Simulink modeling library. Since Simulink uses the MATLAB® computational engine, designers can also use MATLAB toolboxes and Simulink blocksets. SimPowerSystems software belongs to the Physical Modeling product family and uses similar block and connection line interface.

SimPowerSystems software allows you to build and simulate electrical circuits containing linear and nonlinear elements.In this section you

Explore the powerlib library Learn how to build a simple circuit from the powerlib library Interconnect Simulink blocks with your circuit

The circuit below represents an equivalent power system feeding a 300 km transmission line. The line is compensated by a shunt inductor at its receiving end. A circuit breaker allows energizing and de-energizing of the line. To simplify matters, only one of the three phases is represented. The parameters shown in the figure are typical of a 735 kV power system.

33

Circuit to Be Modeled

Building the Electrical Circuit with powerlib LibraryThe graphical user interface makes use of the Simulink functionality to interconnect various electrical components. The electrical components are grouped in a library called powerlib.1. Open the SimPowerSystems main library by entering the following command at the

MATLAB prompt.powerlib

This command displays a Simulink window showing icons of different block libraries.

34

2. Name this block Rs_eq.3. Resize the various components and interconnect blocks by dragging lines from

outputs to inputs of appropriate blocks.

4. To complete the circuit of Circuit to Be Modeled, you need to add a transmission line and a shunt reactor. You add the circuit breaker later in Simulating Transients.

The model of a line with uniformly distributed R, L, and C parameters normally consists of a delay equal to the wave propagation time along the line. This model cannot be simulated as a linear system because a delay corresponds to an infinite number of states. However, a good approximation of the line with a finite number

35

of states can be obtained by cascading several PI circuits, each representing a small section of the line.A PI section consists of a series R-L branch and two shunt C branches. The model accuracy depends on the number of PI sections used for the model. Copy the PI Section Line block from the Elements library into the circuit1 window, set its parameters as shown in Circuit to Be Modeled, and specify one line section.

5. The shunt reactor is modeled by a resistor in series with an inductor. You could use a Series RLC Branch block to model the shunt reactor, but then you would have to manually calculate and set the R and L values from the quality factor and reactive power specified in Circuit to Be Modeled.

Therefore, you might find it more convenient to use a Series RLC Load block that allows you to specify directly the active and reactive powers absorbed by the shunt reactor.Copy the Series RLC Load block, which can be found in the Elements library of powerlib. Name this block 110 Mvar. Set its parameters as follows:

Vn 424.4e3 V

fn 60 Hz

P 110e6/300 W (quality factor = 300)

QL

110e6 vars

Qc 0

Note that, as no reactive capacitive power is specified, the capacitor disappears on the block icon when the dialog box is closed. Interconnect the new blocks as

shown. 6. You need a Voltage Measurement block to measure the voltage at node B1. This

block is found in the Measurements library of powerlib. Copy it and name it U1. Connect its positive input to the node B1 and its negative input to a new Ground block.

36

7. To observe the voltage measured by the Voltage Measurement block named U1, a display system is needed. This can be any device found in the Simulink Sinks library.Open the Sinks library and copy the Scope block into your circuit1 window. If the scope were connected directly at the output of the voltage measurement, it would display the voltage in volts. However, electrical engineers in power systems are used to working with normalized quantities (per unit system). The voltage is normalized by dividing the value in volts by a base voltage corresponding to the peak value of the system nominal voltage. In this case the scaling factor K is

8. Copy a Gain block from the Simulink library and set its gain as above. Connect its output to the Scope block and connect the output of the Voltage Measurement block to the Gain block. Duplicate this voltage measurement system at the node B2, as shown below.

9. Add a Powergui block to your model. The purpose of this block is discussed in Using the Powergui Block to Simulate SimPowerSystems Models.

10. From the Simulation menu, select Start.11. Open the Scope blocks and observe the voltages at nodes B1 and B2.12. While the simulation is running, open the Vs block dialog box and modify the

amplitude. Observe the effect on the two scopes. You can also modify the frequency and the phase. You can zoom in on the waveforms in the scope windows by drawing a box around the region of interest with the left mouse button.

To simulate this circuit, the default integration algorithm (ode45) was used. However, for most SimPowerSystems applications, your circuits contain switches and other nonlinear models. In such a case, you must specify a different integration algorithm. This is discussed in Simulating Transients, where a circuit breaker is added to your circuit.Interfacing the Electrical Circuit with Other Simulink BlocksThe Voltage Measurement block acts as an interface between the SimPowerSystems blocks and the Simulink blocks. For the system shown above, you implemented such an interface from the electrical system to the Simulink system. The Voltage Measurement block converts the measured voltages into Simulink signals.

37

Similarly, the Current Measurement block from the Measurements library of powerlib can be used to convert any measured current into a Simulink signal.You can also interface from Simulink blocks to the electrical system. For example, you can use the Controlled Voltage Source block to inject a voltage in an electrical circuit, as shown in the following figure

.

Measuring Voltages and CurrentsWhen you measure a current using a Current Measurement block, the positive direction of current is indicated on the block icon (positive current flowing from + terminal to – terminal). Similarly, when you measure a voltage using a Voltage Measurement block, the measured voltage is the voltage of the + terminal with respect to the – terminal. However, when voltages and currents of blocks from the Elements library are measured using the Multimeter block, the voltage and current polarities are not immediately obvious because blocks might have been rotated and there are no signs indicating polarities on the block icons. Unlike Simulink signal lines and input and output ports, the SimPowerSystems

connection lines and terminal ports lack intrinsic directionality. The voltage and current polarities are determined, not by line direction, but instead by block orientation. To find out a block orientation, first click the block to select it. Then enter the following command.get_param(gcb,'Orientation')

The following table indicates the polarities of the currents and voltages measured with the Multimeter block for single-phase and three-phase RLC branch and loads (and of the polarity of the capacitor voltage and the inductor current), surge arresters, and single-phase and three-phase breakers.

Block Orientation Positive Current Direction Measured Voltage

right left —> right Vleft – Vright

38

Block Orientation Positive Current Direction Measured Voltage

left right —> left Vright – Vleft

down top —> bottom Vtop – Vbottom

up bottom —> top Vbottom – Vtop

The natural orientation of the blocks (that is, their orientation in the Element library) is right for horizontal blocks and down for vertical blocks.For single-phase transformers (linear or saturable), with the winding connectors appearing on the left and right sides, the winding voltages are the voltages of the top connector with respect to the bottom connector, irrespective of the block orientation (right or left). The winding currents are the currents entering the top connector.For three-phase transformers, the voltage polarities and positive current directions are indicated by the signal labels used in the Multimeter block. For example, Uan_w2 means phase A-to-neutral voltage of the Y connected winding #2, Iab_w1 means winding current flowing from A to B in the delta-connected winding #1.Basic Principles of Connecting Capacitors and InductorsYou have to pay particular attention when you connect capacitor elements together with voltage sources, or inductor elements in series with current sources. When you start the simulation, the software displays an error message if one of the following two connection errors are present in your diagram:

1. You have connected a voltage source in parallel with a capacitor, or a series of capacitor elements in series, like in the two examples below.

To fix this problem, you can add a small resistance in series between the voltage source and the capacitors.

2. You have connected a current source in series with an inductor, or a series of inductors connected in parallel, like in the example below.

39

To fix this problem, you can add a large resistance in parallel with the inductor.Using the Powergui Block to Simulate SimPowerSystems ModelsThe Powergui block is necessary for simulation of any Simulink model containing SimPowerSystems blocks. It is used to store the equivalent Simulink circuit that represents the state-space equations of the SimPowerSystems blocks. You must follow these rules when using this block in a model:

Place the Powergui block at the top level of diagram for optimal performance. However, you can place it anywhere inside subsystems for your convenience; its functionality will not be affected.

You can have a maximum of one Powergui block per model You must name the block powergui

Electrical Terminal Ports and Connection Lines SimPowerSystems modeling environment is similar to that of other products in the Physical Modeling family. Its blocks often feature both normal Simulink input and output ports > and special electrical terminal ports :

Lines that connect normal Simulink ports > are directional signal lines. Lines that connect terminal ports are special electrical connection lines.

These lines are nondirectional and can be branched, but you cannot connect them to Simulink ports > or to normal Simulink signal lines.

You can connect Simulink ports > only to other Simulink ports and electrical terminal ports only to other electrical terminal ports.

Converting Simulink signals to electrical connections or vice versa requires using a SimPowerSystems block that features both Simulink ports and electrical terminal ports.Some SimPowerSystems blocks feature only one type of port.Analyzing a Simple Circuit

Electrical State Variables

40

The electrical state variables are the Simulink states of your diagram associated to the capacitor and inductor devices of the SimPowerSystems blocks. Inductors and capacitors elements are found in the RLC-branch type blocks such as the Series RLC Branch block, Three-Phase Parallel RLC Load block, in the transformer models, in the PI Section Line block, in the snubber devices of the power electronic devices, etc.The electrical state variables consist of the inductor currents and the capacitor voltages. Variable names forSimPowerSystems electrical states contain the name of the block where the inductor or capacitor is found, preceded by the Il_ prefix for inductor currents or the Uc_ prefix for capacitor voltages.You compute the state-space representation of the model circuitl with the power_analyze command. Enter the following command at the MATLAB prompt.

[A,B,C,D,x0,electrical_states,inputs,outputs]=power_analyze('circuit1')

The power_analyze command returns the state-space model of your circuit in the four matrices A, B, C, and D. x0 is the vector of initial conditions of the electrical states of your circuit. The names of the electrical state variables, inputs, and outputs are returned in three string matrices.

electrical_states =

Il_110 MvarsUc_input PI Section LineIl_ sect1 PI Section LineUc_output PI Section LineIl_Z_eqUc_Z_eq

inputs =

U_Vs

outputs =

U_U1U_U2

Note that you could have obtained the names and ordering of the electrical states, inputs, and outputs directly from the Powergui block. See the power_analyze reference page for more details on how to use this function.

Steady-State Analysis

To facilitate the steady-state analysis of your circuit, the powerlib library includes a graphical user interface tool. If the Powergui block is not already present in your model, copy the block from the library into your circuit1 model and double-click the block icon to open it.From the Analysis tools menu of the Powergui block, select Steady-State Voltages and Currents. This opens the Steady-State Tool window where the steady-state phasors voltages measured by the two voltage measurement blocks of your model are displayed in

41

polar form.

Each measurement output is identified by a string corresponding to the measurement block name. The magnitudes of the phasors U1 and U2 correspond to the peak value of the sinusoidal voltages.From the Steady-State Tool window, you can also display the steady-state values of the source voltage or the steady-state values of the inductor currents and capacitor voltages

42

by selecting either the Sources or the States check box.

Refer to the section Measuring Voltages and Currents for more details on the sign conventions used for the voltages and currents of sources and electrical state variables listed in the Steady-State Tool window.

Frequency Analysis

The Measurements library of powerlib contains an Impedance Measurement block that measures the impedance between any two nodes of a circuit. In the following two sections, you measure the impedance of your circuit between node B2 and ground by using two methods: To measure the impedance versus frequency at node B2, you need a current source at node B2 providing a second input to the state-space model. Open the Electrical Sources library and copy the AC Current Source block into your model. Connect this source at node B2, as shown below. Set the current source magnitude to zero and keep its frequency at 60 Hz. Rearrange the blocks as follows.

43

AC Current Source at the B2 Node

Now compute the state-space representation of the model circuitl with the power_analyze command. Enter the following command at the MATLAB prompt.

sys1 = power_analyze('circuit1','ss')

This command returns a state-space model representing the continuous-time state-space model of your electrical circuit. In the Laplace domain, the impedance Z2 at node B2 is defined as the transfer function between the current injected by the AC current Source block and the voltage measured by the U2 Voltage Measurement block.

You obtain the names of the inputs and outputs of this state-space model as follows.

sys1.InputNameans = 'U_Vs' 'I_AC Current Source'sys1.OutputNameans = 'U_U2' 'U_U1'

44

The impedance at node B2 then corresponds to the transfer function between output 1 and input 2 of this state-space model. For the 0 to 1500 Hz range, it can be calculated and displayed as follows.

freq=0:1500;w=2*pi*freq;bode(sys1(1,2),w);

Repeat the same process to get the frequency response with a 10 section line model. Open the PI Section Line dialog box and change the number of sections from 1 to 10. To calculate the new frequency response and superimpose it upon the one obtained with a single line section, enter the following commands.

sys10 = power_analyze('circuit1','ss');bode(sys1(1,2),sys10(1,2),w);

Open the property editor of the Bode plot and select units for Frequency in Hz using linear scale and Magnitude in absolute using log scale. The resulting plot is shown below.

Impedance at Node B2 as Function of Frequency

This graph indicates that the frequency range represented by the single line section model is limited to approximately 150 Hz. For higher frequencies, the 10 line section model is a better approximation.

The system with a single PI section has two oscillatory modes at 89 Hz and 229 Hz. The 89 Hz mode is due to the equivalent source, which is modeled by a single pole equivalent. The 229 Hz mode is the first mode of the line modeled by a single PI section.The propagation time for 300 km is therefore T = 300/293,208 = 1.023 ms and the frequency of the first line mode is f1 = 1/4T = 244 Hz. A distributed parameter line would have an infinite number of modes every 244 + n*488 Hz (n = 1, 2, 3...). The 10 section line model simulates the first 10 modes. The first three line modes can be seen in Impedance at Node B2 as Function of Frequency (244 Hz, 732 Hz, and 1220 Hz).

45

Obtaining the Impedance vs. Frequency Relation from the Impedance Measurement and Powergui Blocks

The process described above to measure a circuit impedance has been automated in a SimPowerSystems block. Open the Measurements library of powerlib, copy the Impedance Measurement block into your model, and rename it ZB2. Connect the two inputs of this block between node B2 and ground as shown.

Measuring Impedance vs. Frequency with the Impedance Measurement Block

Now open the Powergui dialog. In the Tools menu, select Impedance vs Frequency Measurement. A new window opens, showing the list of Impedance Measurement blocks available in your circuit.

In your case, only one impedance is measured, and it is identified by ZB2 (the name of the ZB2 block) in the window. Fill in the frequency range by entering 0:2:1500 (zero to 1500 Hz by steps of 2 Hz). Select the logarithmic scale to display Z magnitude. Select the Save data when updated check box and enter ZData as the variable name to contain the impedance vs. frequency. Click the Update button.

46

When the calculation is finished, the window displays the magnitude and phase as functions of frequency. The magnitude should be identical to the plot (for one line section) shown in Impedance at Node B2 as Function of Frequency. If you look in your workspace, you should have a variable named ZData. It is a two-column matrix containing frequency in column 1 and complex impedance in column 2.

State Variables

The state variables of a Simulink diagram containing SimPowerSystems blocks consist of The electrical states associated to RLC branch-type SimPowerSystems blocks.

They are defined by the state-space representation of your model. See Electrical State Variables for more details about the electrical states.

The Simulink states of the SimPowerSystems electrical models such as the Synchronous Machine block, the Saturable Transformer block, or the Three-Phase Dynamic Load block.

The Simulink states of the other Simulink blocks of your model (controls, user-defined blocks, and other blocksets).

The following picture provides an example that contains the three types of state variables:

47

Initial States

Initial conditions, which are applied to the entire system at the start of the simulation, are generally set in the blocks. Most of the Simulink blocks allow you to specify initial conditions. For the case of the electrical states, the SimPowerSystems software automatically sets the initial values of the electrical states to start the simulation in steady state. However, you can specify the initial conditions for the capacitor voltage and inductor currents in the mask of these blocks:

the Series and Parallel RLC Branch blocks the Series and Parallel RLC Load blocks

The initial values entered in the mask of these block will overwrite the default steady-state parameters calculated by the SimPowerSystems software. In the same sense, you can overwrite initial conditions of the overall blocks by specifying them in the States area of the Configuration Parameters dialog box.See the power_init function reference page for more details on how you can specify initial states for a Simulink diagram with SimPowerSystems blocks.

Specify Initial Electrical States with Powergui

1. Open the Transient Analysis of a Linear Circuit demo by typing power_transient at the command line. Rename the RLC Branch blocks as shown in the next figure.

48

From the Analysis tools menu of the Powergui block, select Initial State Settings. The initial values of the five electrical state variables (three inductor currents and two capacitor voltages) are displayed. These initial values corresponds to the values that the software automatically sets to start the

49

simulation in steady state.

2. Open the Scope block and start the simulation. As the electrical state variables are automatically initialized, the system starts in steady state and sinusoidal waveforms are observed.

3. The initial value for STATE_D state is set to 1.589e5 V. It corresponds to the initial capacitor voltage found in the STATE_D block. Open this block, select the Set the initial capacitor voltage parameter, then specify a capacitor initial voltage of -2e5 V. Click the OK button.

4. Click the From diagram button of the Powergui Initial States Tool to refresh the display of initial states. The initial state of STATE_D block is now set to -2e5 V.

5. Start the simulation. In the second trace of the Scope block, zoom around the transient at the beginning of the simulation. As expected, the model does not start in steady state, but the initial value for the capacitor voltage measured by the Voltage Measurement block is -2e5 V.

6. Select the STATE_A state variable in the Initial States Tool list. In the Set selected electrical state field, set the initial inductor current to 50 A, and click Apply. Open the mask of the STATE_A block, and note that the Set the initial inductor current parameter is selected and the initial inductor current is set to 50 A.

Run the simulation and observe the new transient caused by this new setting.Forcing Initial States to ZeroNow suppose that you want to reset all the initial electrical states to zero without loosing the settings you have done in the previous steps.

1. From the Initial State Tool window, select the To zero check box under Force initial electrical states, then click Apply. Restart the simulation and observe the transient when all the initial conditions starts from zero.

50

2. Open the masks of the STATE_C and STATE_A blocks and note that even if initial conditions are still specified in these blocks, the setting for the initial states is forced to zero by the Powergui block.

A message is displayed at the command line to remind you every time you start the simulation that the electrical initial states of your model are forced to zero by the Powergui block, which overwrites the block settings in your model.

Forcing Initial States to Steady State

Similarly, you can set all the initial states to steady without loosing the settings you have done in the previous steps.

1. From the Initial State Tool window, select the To steady state check box under Force initial electrical states, then click Apply.

2. Restart the simulation and observe that the simulation starts in steady state. A message is displayed at the command line to remind you every time you start the simulation that the electrical initial states of your model are forced to steady state by the Powergui block.

Returning to Block Settings

To return to the block settings, clear both check boxes under Force initial electrical states, then click Apply.

51

Chapter. 5

Simulation on Matlab®/S imulink®

52

5.1 modelling of the solar pv module in matlab/simulink :

A solar pv module is developed in simulink. This module is used as a source for the maximum power point tracker system. The module makes use of the equation of a typical solar cell. The typical model of solar cell is shown in fig.11

I ph=I L+ I d………………………………………………………………………………………(12)

Where I phis photon generated current , I Lis the current generated by the load, I d is the diode current

I d=I ₀(e¿¿( v∗q )k∗T

−1)¿…………………………………………………………………………………(13)

Where I₀ is reverse saturation current of the diode, v i s forward voltage, q is charge, k is Boltzmanns constant and , T is temperature K

We take into consideration the variation of temperature and insolation. The insolation changes affects the photon generated current and has very little effect on the open circuit voltage. When the temperature changes the open circuit voltage and the short circit current vary marginally . I phblkock takes photon generated current and this changes with the insolation.

I ph=G∗I sc……………………………………………………………………………………………..(14)

I sc = the short circuit current of the module at 1000w/m² and G= present insolation /1000

Temperature variation affects the open circuit voltage . the open circuit voltge decreases by about 2.3 mv/cell/degree rise in temperature and the short circuit current increases by about 1 μA/degree rise im temp. these tow effects are taken care of in smulink model of the solar PV module. A series resistance of 8mΩ.

The module voltage and current for different temperature and insolation are simulated . the results are showen in multimetre box.

5.2 MPPT algorithm used

As discussed earlier in the previous chapter amoung the different algorithms perturb and observe is the simplest and gives better results.the algorithm is selected and certain changes are made to it in the presentwork. The flowchart is shown in fig.16.

53

The algorithm reads the value of the current and the voltage from the solar PV module .power is calculated from the measured values. the power and voltage at the kth instant are stored .the next value at (k+1)th instant are measured again and power is calculated from them. If we observe the power voltage curve of solar PV module we see on the right hand side where the voltage is almost constant , the slope of power voltage is negative(dP/dV<0) whereas the left hand side the slope is positive(dP/dV>0).the right side curve is for the lower duty cycle (nearer

54

a

m

to zero)where as the left side curve is for the higher duty cycle (nearer to to unity ).depending on the sign of the dP(P(k+1)-P(k)) and dV(V(k+1)-V(k)), after subtraction of the algorithm decides wheather to increase or to decrease the duty cycle or to reduce the duty cycle .

The algorithm is simple and has only one loop .in perturb and observe algorithms tow loops are implemented. One loop sets the V ref corresponding to the peak power point of the module . the outer PI control loop then implements a feed forward control an dsets the module operating voltage at the V ref value specified by the MPPT algorithm. The use of a PI controller makes the loop faster as compared to that of the the direct duty cycle control method implemented in this work. But still if the sample time is reduced in direct duty cycle control the power tracking can be made faster even in the fast varying climatic conditions.

5.3 dc/dc converters used in mppt systems

A dc/dc converter forms an integral part of any mppt system. Without dc/dc converter no MPPT system are designed. The dc/dc converter cab be either a step down in fig.17 in which the output voltage is then the input voltage or step up converter in fig.18 in which the output voltage is higher than the input voltage.

1 2

g m

Pul se Idea l Swi tchVo =D*Vi

Vi DC Vol ta ge

G3

D=du ty cycl e

=T on /TD

G4

Step Down Converter

CRL

G2 G1

55

Fig.17.Step down or Buck converter (Vo<Vi)

The step down converter the output votage (V₀) is less than the input voltage Vi. the retlation between input and output voltages

V₀=D*Vi……………………………………………………………………………………………………….(15)

Where D is duty cycle of the converter that is the ratio of the t on(time for which the converter remains to switching time t of the converter ).

t

tON time

D ¿t on / t…………………………………………………………………………………………………(16)

Thus by varying the duty cycle the output voltage can changed also the input current and the output current chnges with the change in theduty chcle. Also the impedence seen by the converter input side varies with the duty cycle .

Ri=RL /D…………………………………………………………………………………………………(17)

This property of the converter to transfer impedence is utilized in MPPT. The step down converters can be used where the output voltage needed is less than the input voltage.

The boost converter or the step up converter has the output voltage greater than the input . the voltage transformation ratio is

V ₀=V i / (1−D)………………………………………………………………………………………. ( 18)

By varying D the output voltage can be changed and it is always more than Vi.the advantage of this converter is that the input and the output currentboth are continuos . wheras a step down converter the current is discontinuous. The boost converter can be implemented in the MPPT system where the output voltage of the system required to be higher than the input voltage. Generally in a grid connected sysyems where the MPPT system is part of the boost converter is utilized which maintains a high voltage

even if the array voltage falls . in the present work a step down converter has been simulated a step up converter as it gives the same results as discussed in earlier chapters.

5.4 simulatio of the MPPT system

For the simulation of the MPPT system a step down converter model is developed in simulink using power systems block set. The values of the components where carried out from the design procedures given in [10].

At the switching freq 20kHz, th value of the components selected are :

L= 330 μH

C= 440 μF

RL=2(60 W )

f= 20 kHz

the swich used was an ideal switch, with low switching and ON state loss.

The solar PV module developed was used as the source.

The simulink setup of the MPPT system is shown in fig. 19. the MPPT block takes the voltage and current through the multimetre. The MPPT block contains thealgorithm explained in the previous chapter (3.2) the insolation and the temperatureare kept fixed and are not varied. The simulink implementation of the algorithm is shown in fig.20. the logic is developed according to the flowchart. Direct duty cycle method is implemented . the algorithm outputs a signal which has avalue between 1 & 0.

This signal is then given to the PWM generator which consists of a saw tooth generator and comparator. The algorithm output signal is compared with a high frequency saw tooth wave form . the output of the comparator is a pulses of high frequency waves which are used to drive the switch. The algorithm gives the duty cycle outputand hence when peak power is reached the algorithm perturbs around the peak power.

.

Chapter .6

Results of the simulation

6.1 the results for the simulation where carried out for starting from a higher duty cycle (left half of the PV curve)that is unity and at some other initial duty cycle value which lies in the right half of the PV curve. the results for both the caseswhere obtained in simulink. The module parameters where kept constant. the results are shown in the fig.21 and fig.22.

From the results it is inferred that the algorithm tracks the peak power and also from both the directions of the PV curve(right half and left half). A slow tracking of the peak power is observed .

Chapter.7

Conclusions and future scope

7.1 Conclusions

1].Power output of module improves by about 100%( doubles) with the MPPT system than it

was with out the MPPT system.

2].The power delivered to the load in case of step-down and step up converter is almost same.

Only difference that was observed was with the output voltage. In case of steps down

converter the output voltage falls to about 3V which is less than what is required for most of

the system and in the step up converter the output voltage is always more than 15V ,hence

higher voltage level is desirable in most of the cases.

3].

7.2 Future scope

Perturb and observe (P&O) algorithm for the peak power tracking is explained in the present project report. Simulink models of the algorithms other than the P&O are explained in chapter 3, which can be developed and tested on real time platform.

1. Development of microcontroller based dedicated MPPT controller for solar PV module based on the present algorithm. This can be a low cost embedded controller.

2. Automatic recording and monitoring of temperature and insolation level on the module to predict the peak power of the tracker.

3. Implementing the axial tracking with the electrical (MPPT) tracking on a solar PV module and checking its response on the module power output.

4. Implementing other algorithms as explained in chapter 3 on an real time platform and checking their responses.

5. A whole stand alone system including the MPPT system and the inverter system can be developed using the real time platform.

Chapter. 8

References

1].Chihchiang Hua, ,Jongrong Lin, and Chihming Shen,“Implementation of a DSP- Controlled Photovoltaic System with Peak Power Tracking”,IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 45, NO. 1, FEBRUARY 1998 pp 99-107.

2].Chihchiang Hua and Chihming Shen, “Control of DC/DC Converters for Solar EnergySystem with Maximum Power Tracking”.

3].Joe-Air Jiang, Tsong-Liang Huang, Ying-Tusg Hsiao and Chia-Hong Chen “ Maximum power tracking for photovoltaic power systems”.

4].D. P. Hohm, M. E. Ropp,“Comparative Study of Maximum Power Point Tracking Algorithms Using an Experimental, Programmable, Maximum Power Point Tracking Test Bed”,IEEE,2000.pp.1699-1702.

5].Mohammad A. S. Masoum, Hooman Dehbonei, and Ewald F. Fuchs, “Theoretical and Experimental Analyses of Photovoltaic Systems With Voltage- and Current-Based Maximum Power-Point Tracking”, IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 17, NO. 4, DECEMBER 2002.

6].Xuejun Liu and A.C.Lopes,,“An Improved Perturbation and Observe Maximum PowerPoint Tracking Algorithm for PV Arrays” IEEE PESC ‘2004, pp.2005-2010.

7]. T. Markvart, “ Solar Electricity”, John Wiley & Sons.

8]. N. Mohan et al., “Power Electronics—Converter, Applications, and Design”. New York: Wiley.

9]. www . i e e e x p l o r e . ie e e . or g

10]. ww w . m at hw o r k s. c om

12].Simulink manuals.