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ABSTRACT

 

The performance of photovoltaic (PV) module is dependent on shading conditions of the cells. This research work is aimed at developing an improved PV-model considering the various degree of shading on PV-cells connected in a PV-module. This is based on modelling the different degrees of shading of cells in a module into the general model by introducing degree of shading parameter. A MATLAB-based graphical user interface (GUI) is developed using Artificial Fish Swarm Algorithm (AFSA). This is used to accurately predict current-voltage (i-v) curves, power-voltage (p-v) curves, maximum power point values, short-circuit current and open-circuit voltage. A set of simulation scenarios involving uniform and non-uniform shading across PV-modules with/without bypass diodes were carried out in order to demonstrate the effectiveness of the developed models and their accuracy. The developed AFSA based model was compared with the conventional dynamic programming (DP) based model, using the output parameters of the PV-system presented in the work of El-Saady et al. (2013) to evaluate the performance of the proposed approach using three performance metrics (open circuit voltage, short-circuit current and maximum power point). Results from AFSA based model showed 59.7303W, 3.8A and 21.0897V for maximum power point, short-circuit current and open circuit voltage respectively. This showed that AFSA based model produced increase in accuracy improvement of 5.1%, 0.03% and 0.22% over DP based model. Even though the developed AFSA based approach possessed some degree of truncation error, it has been shown to outperform the conventional DP based approach.

 

TABLE OF CONTENTS

DECLARATION II CERTIFICATION III DEDICATION IV ACKNOWLEDGEMENT V ABSTRACT VI LIST OF FIGURES XI LIST OF TABLES XIII LIST OF ABBREVIATION XIV APPENDIX X CHAPTER ONE : INTRODUCTION 1 1.1 BACKGROUND 1 1.2 MOTIVATION 5 1.3 STAMENT OF PROBLEM 5 1.4 AIMS AND OBJECTIVES 6 1.5 DISSERTATION ORGANIZATION 6 CHAPTER TWO : LITERATURE REVIEW 8 2.1 INTRODUCTION 8 2.2 REVIEW OF FUNDAMENTAL CONCEPTS 8 2.2.1 PV Cell Operation 8
2.2.2 PV Cell Model 11
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2.2.3 Diodes and their Functions 14
2.2.4 Effects of Bypass Diodes on Photovoltaic Cells 14
2.2.5 Maximum Repetitive Reverse Voltage ( RRM V ) 17
2.2.6 Maximum Power Point Current (Impp) and Voltage (Vmpp) 17
2.2.7 Ideality and Fill Factor 17
2.2.8 Solar Cell Efficiency 18
2.2.9 Resistance 18
2.2.10 Maximum PowerPoint (MPP) 19
2.3 REVIEW OF SIMILAR WORKS 26
CHAPTER THREE : MATERIALS AND METHODS 34
3.1 INTRODUCTION 34
3.2 METHODOLOGY 34
3.3 PROPOSED MATHEMATICAL MODEL OF PV-CELLS WITH SHADING EFFECTS 35
3.4 PROPOSED AFSA BASED APPROACH FOR I-V CURVES 39
3.5 PROPOSED AFSA BASED APPROACH FOR P-V CURVES 46
3.6 PROPOSED AFSA APPROACH FOR MAXIMUM POWER POINT 47
3.7 PROPOSED DP BASED APPROACH FOR PV –ARRAY 50
3.8 THE PROPOSED MODEL FOR BYPASS DIODE IN PV-MODULES 52
3.9 1NFLECTION IN I-V CURVE 52
3.10 SHADING EFFECT ON PV-SYSTEM WITH BYPASS DIODES 53
3.11 PROPOSED APPROACH FOR P-V CURVES WITH BYPASS DIODE EFFECT 56
3.12 THE DEVELOPED PV- ARRAY ANALYSIS SIMULATOR 59
3.13 PROPOSED PV- ARRAY ANALYSIS ALGORITHM 60
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3.14 SIMULATION 63 CHAPTER FOUR : RESULT AND DISCUSSION 64 4.1 INTRODUCTION 64 4.2 PROPOSED MODEL TESTING RESULTS 64 4.2.1 I-V Curves with Varying Degree of Shading 64 4.2.2 P-V Curves with Varying Degree of Shading 65 4.2.3 Output Characteristics of PV-Array in Different Configuration 66 4.2.4 Effect of Bypass-Diodes on the Output Characteristics of PV-Array 71 4.2.5 Comparison Case A 76 4.2.6 Comparison Case B 77 CHAPTER FIVE : CONCLUSION AND RECOMMENDATION 79 5.1 CONCLUSION 79 5.2 SIGNIFICANT CONTRIBUTIONS 79 5.3 RECOMMENDATION 80 5.4 LIMITATION 81 REFERENCES 82

 

 

CHAPTER ONE

 

INTRODUCTION
1.1 Background
The evolution in technology and the awareness of global warming have drawn attention towards the use of solar photovoltaic cells as an alternative source of electric power (Diaf et al., 2011). A Photovoltaic (PV) system generates electricity by the direct conversion of solar energy (Theocharis et al., 2012). Photovoltaic systems provide electricity for home appliances, villages, water pumping, desalination and many other applications (Said et al., 2012). Photovoltaic output power depends on many factors, such as sun position, weather conditions, module temperature, thermal characteristics, module material composition, mounting structure, and shading (Platzer, 2012) A simple solar PV system is shown in Figure 1.1
Figure 1.1: A Simple PV System (Thongam & Jaiswal, 2015)
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Some of the advantages of solar photovoltaic are (Jayakumar, 2009):
1. Solar PV provides clean-green energy and available almost everywhere there is sunlight.
2. It is appropriate for smart energy networks with Distributed Power Generation-DPG, as next generation power network structure.
3. Solar PV cost is currently on a fast reducing track. Consequently Solar PV has indeed a highly promising future both for economic variability and environmental sustainability
4. Solar PV is totally silent, producing no noise at all, which makes it a perfect solution for urban areas and for residential applications.
5. Solar PV has no mechanically moving parts, except in cases of sun-tracking mechanical bases. Consequently it has far less breakages or requires less maintenance than other renewable energy systems.
6. Solar PV, through photoelectric phenomenon, produces direct electricity.
Despite the advantages of Solar PV, it also has some limitations which include (Jayakumar, 2009);
1. Fragility, which means can be damaged easily.
2. Intermittency and unpredictability of solar energy due to weather, makes solar panels to shaded.
3. Multiple components.
Shading is an effect that is produced when sun light meant to directly hit the PV-cell is obstructed by an opaque object (Parida et al., 2013). Shading obstructions can be classified as soft or hard sources. Soft sources such as a tree leave, a roof vent, a chimney or other item which shades from a distance, are those in which the shadowing is diffused or dispersed (Kelly & Gibson, 2009).These soft sources significantly reduce the amount of light reaching the cells of a module. Hard sources are defined as those that stop light from
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reaching the cells, such as a blanket, tree branch, etc sitting directly on top of the glass
(Briggs, 2012). Some shading types can cover an entire single cell of a module, some can
cover an entire module of the array, and some create various shading pattern on either
strings, module, or cells (Morais et al., 2010). Measuring the extent of the shade on a solar
array may be challenging due to the fact that shadows move as the sun position moves
throughout the day and year. Shading of photovoltaic systems can cause high loss in
performance (Lagorse et al., 2010). There are different types of shading, which include:
1. Direct Shading: In this case, a shadowing object is placed close to modules and shades
the PV array constantly. The closer the shading object is to the array, the darker the
shade is and the less diffuse light reaches the module surface, the more problematic the
situation gets (Jiang et al., 2011).
2. Temporal Shading: This is caused by natural conditions, like snow, leaves, soiling,
etc. This effect is especially important in ground mounted systems in rural areas, where
the PV arrays come much easier in contact with dust. In snowy regions, horizontal
arrangement of the module is recommendable in order to minimize losses (Haeberlin,
2007).
3. Self-Shading: A bad system design might cause shading on modules due to other
modules that have been placed ahead. As a rule of thumb, the modules located in a row
must be separated from each other approximately 4-6 times the height of the tilted
module and under this condition, mutual shading is avoided (Firth et al., 2010).
4. Whole and Partial Shading: Whole shading and partial shading refer to cell shading
ratio
ce llarea
shadedarea
.
.Whole shading and partial shading reference to the threshold point
below which there is insufficient irradiance to generate cell voltage (Whole Shade) and
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above which there is sufficient irradiance to generate cell current (Partial Shade).Whole or partial shading of a cell will lead to different effects on module voltage or current or both (Farret & Simoes, 2006).
Figure 1.2 shows typical PV cells in a PV module under different shading conditions
Figure 1.2: PV–Cells in a PV-Module under Different Degrees of Shading
Effect of shading as a significant research issue in optimizing PV output power has been established (Alsayid et al., 2013a; Kelly & Gibson, 2009; Seyedmahmoudian et al., 2013).Some researchers have considered shading of certain group of cells or modules in a PV-array with uniform shading pattern (Khalaf et al., 2014; Ramana & Jena, 2015; Sikiru, 2007). This research proposes the development and analysis of improved PV-array with shading effects which include introduction of degree of shading parameter and use of Artificial Fish Swarm Algorithm (AFSA) for determining the output characteristics, because it has presented capability to avoid local optimum in order to achieve global optimization. The focus of developing the improved PV-model is to help in analyzing the effect of varying degrees of shading across in the individual cells in a PV-module.
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1.2 Motivation
Shading conditions affect the performance of Photovoltaic cells. PV-cells must be operated at their maximum power point, for optimal utilization. However, maximum power point is not steady rather it varies with shading degrees, and other degrading effects. Existing models‟ current and voltage compromises that all the PV-cells exhibit homogeneity for same insolation conditions. In practice, these assumptions are not absolutely correct because of non-uniformity caused by environmental conditions. Therefore, it is almost unachievable to have uniform insolation across the PV-cells. Having these variations of the characteristics of the PV-arrays due to degree of shading, there is demand to effectively determine the Maximum Power Point using high efficient convergent intelligent technique.
1.3 Statement of Problem
Photo-voltaic cell is an indispensable part in the conversion of sun‟s power into electricity. It provides useful applications in enabling humanity to make use of sunlight in a clean and highly versatile way. Photovoltaic modeling is a challenge due to shading. Most of the PV-models currently available in the open literature are well adequate for uniform shading pattern of PV-modules. However, the accuracy of the output characteristics of the existing models are often been affected by the effect of the degree of shading across individual cell. In order to overcome this shortcoming, an improved PV-array model that incorporates a parameter that can handle the varying degree of shading is proposed in this research as a means of addressing the limitations that are inherent in the existing models.
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1.4 Aim and Objectives
The aim of the research is to develop and analyze an improved PV-array model, while considering the effects of varying degrees of shading across the individual cells of a PV-module. In achieving the aim, the following are the set of objectives:
1. To incorporate a shading parameter into the conventional PV-array model that will account for varying degree of shading across individual cells of a given PV-module;
2. To develop Artificial Fish Swarm Algorithm (AFSA) based model for determining the output characteristics (I–V curve; P–V curve; and Maximum Power Point) of PV-cells connected in various configurations with and without bypass diode;
3. To develop Matlab-based AFSA and DP graphical user interface (GUI) models in order to carry out a comparative analysis using the following performance metrics for the validation of the developed model: open-circuit voltage, short-circuit current and maximum power point.
1.5 Dissertation Organization
The general introduction has been presented in Chapter One. The rest of the chapters are structured as follows: First, detail review of related literature and relevant fundamental concepts about PV-Cell Operation, PV-Array, PV-Cell Model, Maximum Power Point, Maximum Power Point Algorithms, Artificial Fish Swarm Algorithm (AFSA) are carried out in Chapter Two. Second, mathematical model for the proposed PV-array output characteristics coupled with that of the improved AFSA algorithm, the steps for the development of the proposed AFSA based I – V curve, P – V curve, and MPP evaluation Algorithm are presented in chapter Three. Third, the analysis and discussion of the result
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are shown in Chapter Four. Finally, conclusion and recommendations of further work makes up the Chapter Five. The list of cited references and MATLAB codes in the appendices are provided at the end of this dissertation.

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