Maximum Power Point Tracking of Polycrystalline Photovoltaic Cells Based on Optimized Adaptive Differential Conductance Technique

ABSTRACT Maximum power point tracking of a polycrystalline Photovoltaic (PV) cell using an Optimized Adaptive Differential Conductance (OADC) technique was proposed in this work. This technique enhances the optimum power transfer from PV panel to the load by reducing the tracking latency and increasing convergence efficiency and speed unlike the conventional Incremental conductance. In this research work, current at maximum power point and voltage at maximum power point can be calculated without data sheet by using an algorithm developed for it. The performance of the algorithm developed in this work was evaluated by simulating the maximum power point tracking of PV cell at irradiance of 1000W/M2 , 800W/M2 , and 600W/M2 at 298k and some fixed temperatures. Based on the simulation results, it was observed that the impedance of the panel varied inversely as the irradiance while impedance of the load is not affected by irradiance. This technique was also validated by comparison with conventional incremental conductance technique. The resultant conductance of this technique is 0.0030 mho at maximum power where as conventional has -0.0418 mho which is less than zero. This technique has a relative improvement of 6.0558% compared to conventional incremental conductance technique. The simulation was done using Matrix Laboratory (MATLAB).

TABLE OF CONTENTS

PRELIMINARY PAGES

COVER PAGE - - - - - - - - - I

APPROVAL PAGE - - - - - - - - - II

CERTIFICATION - - - - - - - - III

DEDICATION - - - - - - - - - IV

ACKNOWLEDGMENT - - - - - - - - V

ABSTRACT - - - - - - - - - - VI

TABLES OF CONTENT - - - - - - - - VII

LIST OF FIGURES - - - - - - - - XI

LIST OF TABLES - - - - - - - - - XIII

LIST OF ABBREVIATIONS - - - - - - - XVI

DEFINITION OF KEY TERMS - - - - - - - XVIII

LETTERS USED AND THEIR MEANINGS - - - - - XIX

CHAPTER ONE: INTRODUCTION

1.1. Background of the Study - - - - - - - 1

1.2. Problem Statement - - - - - - - - 5

1.3. Research Objectives - - - - - - - - 6

1.4. Scope of the Study - - - - - - - - 7

1.5. Significance of the Study- - - - - - - - 7

1.6. Research Methodology - - - - - - - - 7

1.7. Plan of Thesis - - - - - - - - - 8

CHAPTER TWO: LITERATURE REVIEW

2.1. Overview of Maximum Power Point Tracking - - - - - 9

 2.1.1. Structure of the Solar Cell - - - - - - - 11

 2.1.2. Operating Principle of PV Cell - - - - - 13

2.2. Maximum Power Point Tracking- - - - - - - 14

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 2.2.1 Theory of Maximum Power Point Tracking - - - - 15

 2.2.2 Principles of MPPT Technique - - - - - - 16

 2.2.3 Incremental Conductance Technique - - - - - 17

2.3. Review of Related Literature - - - - - - - 20

 2.3.1 Non-Intelligence Maximum Power Point Tracking Techniques - - 20

 2.3.1.1 Incremental Conductance (INC) Technique - - - - 21

 2.3.1.1 Incremental Conductance Algorithm - - - - 22

 2.3.1.1.2 An Improved Incremental Conductance (IINC) Technique - 24

2.3.1.2. Perturb and Observe (P&O) Technique - - - - - 27

 2.3.1.2.1. Adaptive Perturb and Observe (AP&O) Technique - - 31

 2.3.1.3. Fractional Short Circuit Current (FSCC) Technique - - 37

 2.3.1.4 Fractional Open Circuit Voltage (FOCV) Technique - - - 38

 2.3.1.5 A Variable Indicator and Scaling Factors Technique - - - 39

 2.3.1.6 Centralized, Distributed and Reconfiguration Technique

 for Mismatching Conditions - - - - - - 39

 2.3.1.7 Random Search Method (RSM) - - - - - - 40

 2.3.1.7.1 Application of RSM for GMPP for PV Systems- - - 41

 2.3.1.8 Dividing Rectangular Search (DIRECT SA) Technique - - - 42

 2.3.2 Intelligent MPPT Techniques - - - - - - 43

 2.3.2.1 Fuzzy Logic Control (FLC) Technique - - - - 43

 2.3.2.1.1 A Takagi–Sugeno (T-S) Fuzzy-Model Technique - - 47

 2.3.2.2 Artificial Neural Network (ANN)- - - - - 48

 2.3.2.3 Particle Swamp Optimization (PSO) Technique - - - 49

 2.3.2.3.1 Improved Particle Swarm Optimization (IPSO) - - 51

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2.4 Comparison of the Existing MPPT Techniques - - - - - 54

2.5. Summary of the Reviewed Existing Technique Discussed in this Thesis - 57

CHAPTER THREE: RESEARCH METHODOLOGY AND PROPOSED MODEL

3.1. Introduction - - - - - - - - - 59

3.2. Initial Model - - - - - - - - - 59

3.3. Proposed Optimized Adaptive Differential Conductance Technique - - 60

3.4: Proposed Model for the Optimized Adaptive Differential

 Conductance Technique - - - - - - - - 67

CHAPTER FOUR EVALUATION, RESULTS AND DISCUSSION

4.1. Ideal Conditions for Incremental Conductance Technique - - - - 70

4.2. Simulation of the Developed Technique - - - - - - 71

4.3. Simulation Parameters - - - - - - - - 72

4.4. Simulated Data - - - - - - - - - 73

4.5. Results and Discussions - - - - - - - - 74

4.6. Model Validation - - - - - - - - 78

 4.6.1: Maximum Power Performance Validation - - - - 79

4.7. Performance Metrics - - - - - - - - 80

CHAPTER FIVE: SUMMARY, RECOMMENDATION AND CONCLUSION

5.1. Summary - - - - - - - - - 81

5.2. Achievements - - - - - - - - - 81

5.3. Recommendation - - - - - - - - - 82

5.4. Conclusion - - - - - - - - - 82