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ABSTRACT

The complexity and large number of computations involved in power flow and reconfiguration analysis of large distribution networks necessitates the need for the improvement of power flow and reconfiguration techniques. In this research work, a GPS based method is used in modeling Azare distribution network and in selecting the most appropriate positions of Tie branches (required for network reconfiguration). Radial distribution network power flow and reconfiguration algorithms are developed based on improved Backward-Forward Sweep (BFS) and All Spanning Trees of Undirected Network Graph (ASTUNG) techniques respectively.MATLAB GUI based simulators are also developed for power flow and reconfiguration analysis. The developed simulators are used in simulating power flow and reconfiguration on the Azare distribution network. A voltage profile improvement of 64.11% and a total real power loss reduction of 54.4% are achieved in the optimum configuration compared to the original configuration. Finally, the effectiveness of the developed power flow simulator is also demonstrated by testing it using the Standard IEEE 30 and 33 bus networks and comparing the results with those obtained in other similar literatures; while the effectiveness of the reconfiguration simulator isdemonstrated using the standard IEEE 33 bus network. The developed reconfiguration simulator was able to improve the voltage profile of the standard 33 buses IEEE radial network by 65.7% and reduce its total real power loss by 56.17%; and when compared with other similar literatures, an improvement of 14.23% is made in voltage profile while a reduction of 0.31% is achieved in power loss. All computations and simulations were performed using MATLAB V.7.0 Software.

 

 

TABLE OF CONTENTS

 

TITLE PAGE i DECLARATION ii CERTIFICATION iii DEDICATION iv ACKNOWLEDGEMENT v ABSTRACT xvii
CHAPTER ONE: GENERAL INTRODUCTION
1.1 General Background 2
1.2 Azare Distribution Network 4
1.3 Azare Electricity Supply Systems 8
1.4.Azare Electricity Consumers 10
1.5. Aim and Objectives 11 1.6 Problem Statement 12 1.7 Methodology 13 1.8Significant Contributions 14 1.9 Thesis Organization 15 CHAPTER TWO: LITERATURE REVIEW 2.1 Introduction 16 2.2Review of Fundamental Concepts 16 2.3 Electric Power Systems 16 2.4 Distribution System 17 2.4.1 Types of Distribution System 18 2.4.1.1 Primary Distribution System 19
2.4.1.2 Secondary Distribution System 19 2.5 Network Reconfiguration 20 2.6 Single Phase Representation of a Balanced Three Phase System 21 2.7 Per-Unit (pu) System 23 2.8 Bus Classification 27 2.9. Conventional Power Flow Techniques 28 2.10. Backward-Forward Sweep (BFS) Technique for Power Flow Analysis 32 2.11 All Spanning Trees of Undirected Network Graph (ASTUNG) Technique34 2.11.1 Candidate solutions 36 2.11.2.Infeasible Solution 37 2.12. Model of network reconfiguration 38 2.13. Load Model 39 2.14 Ampacity 40 2.15. Load Balancing 41 2.15.1. Model of load balancing 41 2.16 Voltage Stability index (VSI) 42 2.17. Voltage Drop 42 2.18 Review of Similar Work 43 CHAPTER THREE: METHODS AND MATERIALS 3.1 Introduction 53 3.2 Data Collection 53 3.3 Assumptions 54 3.4 Azare Distribution Network Map 54 3.4.1 Tie Switch Placement 57 3.5 Proposed Power Flow Model 60 3.5.1 Information Matrix (IM) 62
3.5.2 Bus Incident Matrix 63 3.5.3 Bus Injected Power (Sinj) 65 3.5.4 Power Loss (Sloss) 65 3.5.5 Voltage Deviation (VD) 66 3.5.6 Significant Features of the Proposed Power flow Approach 68 3.5.7 Proposed Power Flow Algorithm 69 3.6 Proposed Reconfiguration Model 72 3.6.1Candidate Solution Generator (CSG) 73 3.6.2 Reduced Network Graph Information Matrix (RNGIM) 74 3.6.3Significant Features of the Proposed Reconfiguration Approach 79 3.6.4. Proposed Reconfiguration Algorithm 80 3.7 Matlab GUI for Power Flow and Reconfiguration Simulators 83 3.7.1 Power Flow and Reconfiguration GUI Design and Programming 83
CHAPTER FOUR: RESULT ANALYSIS AND DISCUSSIONS 4.1 Introduction 88 4.2 Simulation 88 4.3. Voltage Profile 91 4.3.1 Voltage Profile Improvement 95 4.4Voltage Stability Index (VSI). 95 4.5 Solution Search 97
4.6 Power Losses 99
4.7Validation 102 4.7.1 Standard 30 buses IEEE Network 103 4.7.2 Standard 33 buses IEEE Network 104
CHAPTER FIVE: CONCLUSION, RECOMMENDATION 5.1 Introduction 108 5.2 Conclusion 108 5.3Recommendation 109 5.4 Limitation 110 REFERENCES 111 APPENDICES APPENDIX A Substations Data, Network Data, and GPS Data 115 APPENDIX B m. File: Main Function “RADFLOW” 125 APPENDIX C m. File: Sub-Function “sortbus” 127 APPENDIX D m. File: Sub-Function “sortbus” 128 APPENDIX E m. File: Sub-Function “wizbus” 129 APPENDIX F m. File: Sub-Function “VDROP” 130 APPENDIX G m. File: Sub-Function (New Configuration Line Data Generator) 131 APPENDIX H m. File: Main Function “optconfig” 134 APPENDIX I m. File: Sub-Function “configs” 140 APPENDIX J m. File: Main Function “gui_radflow” 144 APPENDIX K m. File: Main Function “gui_optconfigs” 151 APPENDIX L Conductor Ampacity and GMD Factor 155 APPENDIX M

Project Topics

 

CHAPTER ONE

GENERAL INTRODUCTION
1.3 General Background
Distribution system is the largest portion of the electrical power system. It can be defined as the part of a power system that distributes power to various customers in ready-to-use form at their place of consumption .(Ramesh et al, 2009). Optimal planning and design of the distribution systems involves network reconfiguration for distribution loss minimization, load balancing under normal operating conditions and fast service restoration to minimize the zones without power under failure conditions (Muhtazaruddin et al., 2014). Most of the distribution networks are configured radially which simplifies over-current protection of the feeders (Muhtazaruddin et al., 2014). The manual or automatic switching operations are performed to vary the configurations. As the operating conditions change, the purposes of network reconfiguration are (Muhtazaruddin et al., 2014):
(i) To minimize the system power loss;
(ii) To balance the loads in the network.
(iii) To improve the voltage profile.
Power flow analysis is the determination of steady state conditions of a power system for a set of specified power generations and load demand. It involves the solution of a set of non-linear power flow equations (Ashokumar et al., 2009). Applications, especially in the fields of power system optimization and distribution automation, require repeated fast power flow solutions (Ashokumar et
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al., 2009). Due to the large number of interconnections and continuously increasing demand, the size and complexity of the present day power systems, have grown tremendously (Cossi et al, 2012). In the last few decades efficient and reliable power flow techniques such as Gauss Seidel (GS), Newton-Raphson (NR) and fast decoupled power flow (FDPF) have been developed and widely used for powers system operation, control and planning. However, it has repeatedly been shown that these methods may become inefficient in the analysis of distribution systems due to the following facts (Kashem et al,2010).
1. Distribution networks can be numerically ill-conditioned (network with high conductor losses) due to wide range of X/R ratios and the inherent radial structure.
2. Distribution power flow equations are different in nature from transmission power flow equations
The Global Positioning System (GPS) is a technology, which provides accuracy and flexibility in the determination of stationary or moving spatial objects (Beyers et al., 1996). In electrical power distribution system, it is used for finding the location of any object e.g. poles, substations, transformers, tracking of routes etc. It gives the position in form of latitude and longitude, which can directly be imported on computer screen.GPS are becoming very effective tools for GIS data capture (Boulaxis & Papadopoulos, 2002). The GPS can easily be linked to a laptop, computer in the field, and, with appropriate software. Users can also have
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all their data on a common base with very little distortion. Thus GPS can help in several aspects of construction of accurate and timely GIS databases.
Researchers have developed various techniques such as: modified-NR {Zhang et al, 2011); modified-FDNR (Aravindhababu et al, 2010); and Layer-By-Layer Backward-Forward Sweep (BFS) (Yan et al., 2003), for radial distribution network power flow analysis. Furthermore, techniques such as: Evolutionary Algorithm (Amasifen et al, 2014); Artificial Intelligence Algorithm (AIA) (Qlu et al, 2014); improved binary particle swarm optimization (IBPSO) (Sedighizadeh et al, 2014); All Spanning Trees of Undirected Network Grapgh (ASTUNG) (Zhang et al, 2014); and refined genetic algorithm (RGA) (Zhu, 2010), have also been developed for radial distribution network reconfiguration analysis. BFS and ASTUNG techniques are relatively flexible, less complex, and easier to implement as compared to all other power flow and reconfiguration techniques respectively. The major setback in most of the power flow and reconfiguration techniques is that, they eventually become too complex to apply as the network size increases and cannot be easily implemented in computer as tool for power flow and reconfiguration analysis. The flexibility and robustness of some of these techniques can be improved using numerical analysis techniques rather than complex differential equations.
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In this research work, a radial distribution network is mapped using GPS, and a number of suitable position for tie-switches needed for network reconfiguration is determined. Then, the unique structure of the radial distribution system is exploited in order to come up with fast and flexible radial distribution system power flow and reconfiguration techniques based on Backward-Forward-Sweep (BFS) and All Spanning Trees of Undirected Network Graph (ASTUNG) respectively. 1.2 Azare Distribution Network
Azare as the major and most populated town in Katagum L.G.A. of Bauchi State has the highest number of consumers of electricity in Katagum zone of Bauchi State (www.google.com/population/azare/katagum/bauchi/niguria). Plate 1.1 shows the complete geographical map of Bauchi state showing the various local governments and the major road map.
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Plate 1.1: Map of Bauchi State, Showing the Major Roads Network and Various
Local Governments (www.google.com/zip-codes/bauchi-state/nigeria )
KATAGUM ZONE
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Azare has a single 33/11kV injection substation which is being fed from a 132/33kV injection substation located within its vicinity. The schematic diagram of Azare 33kV network is shown in Figure 1.1. All, except the Azare injection substation power transformer in Figure 1.1, are 33/0.415kV distribution transformers which are dedicated to special consumers (Factories, BTSs, Institutions, Hospitals, etc.).
Figure 1.1: Schematic Diagram of the 33kV Distribution Network of JEDPLC, Azare, Dec. 2013
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The Azare Injection Substation has a 7.5MVA, 33/11kV power transformer. 2x11kV main feeders radiate outward from the substation to serve two categories of customers on the 11kV network. The two categories of customers are:
1. The GRA Feeder Consumers.
2. The Town Feeder Consumers.
The complete network diagram of the two main feeders and their laterals are shown in Figures 1.2 and 1.3 respectively.
Figure 1.2: Schematic Diagram of the 11kV GRA Main Feeder and its Laterals of JEDPLC, Azare, 2013
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Figure 1.3: Schematic Diagram of 11kV Town Main Feeder and its Laterals of JEDPLC, Azare, 2013 1.3 Azare Electricity Supply Systems
The route of power supply to JEDPLC, Azare can easily be described by Figure 1.4. The power supply originates from Mando Regional Transmission Station at Kaduna and runs through a Sub-regional Transmission Station at Kano (TCN. Kumbotso), a Sub-transmission Station at Jigawa (TCN. Dutse) and finally
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terminate at TCN, Azare. The Schematic diagram of TCN, Azare substation is shown in Figure. 1.5.
Figure 1.4: The Schematic Diagram of the Electricity Supply-Chain to JEDPLC, Azare
Figure 1.5: The Schematic Diagram of TCN, Azare
COUPLER
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1.4 Azare Electricity Consumers Even though, Azare has a 2MVA, 11/0.415kV Transformer which has not been in service for the past 5 years (the company that owns it has not been operational), its electricity is majorly consumed by house-hold appliances due to the fact that only a few number of small and medium scale industries exist. Currently, the largest installed and operating distribution transformer (33/0.415kV) has a capacity of 830kVA. It provides service to GILMO Water Board and a few numbers of other customers within its vicinity. This distribution transformer supplies not more than 50% of its rated capacity. The boundaries of Azare are rapidly expanding due to continuous construction of houses. This results in continuous increase in its average number of electricity consumers. The Percentage-load contributed by each of the categories is shown in Figure 1.6.
Figure 1.6 Percentage Load contributions of the Main Load Categories in Azare, 2013
RESIDENTIAL LOAD65%
COMMERCIAL LOAD15%
SMALL & MEDIUM INDUSTRIES, 15%
ADMINISTRATIVE LOAD5%
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1.5. Aim and Objectives The aim of the proposed research work is to model a radial distribution network, and develop robust computer aided power flow and reconfiguration techniques based on improved Backward-Forward Sweep (BFS) and All Spanning Trees of Undirected Network Graph (ASTUNG) techniques respectively. In achieving this, the following objectives are met.
1. To collect relevant data from Azare distribution network and organizing them;
2. To develop improved power flow and reconfiguration models and algorithms.
3. To design and program MATLAB GUIs based on the developed power flow and reconfiguration algorithms;
4. To simulate power flow and reconfiguration on Azare distribution network;
5. To validate the developed models and algorithms using standard IEEE 30 and 33 bus radial distribution networks.
1.6 Problem Statement
The continuous growth in electrical energy demand and pressing need for better quality of service has necessitated the need for continuous radial distribution network analysis. Power flow and reconfiguration analysis form the bases of network reconditioning for safety loss reduction and reliability. The major challenge is that, power flow and reconfiguration analysis involves iterative
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computations that are time consuming and gets more complex as the network size (number of nodes) increases. Various techniques have been developed by researchers to address the stated problems. The flexibility and robustness of some of these techniques can be improved by developing a robust computer aided techniques for radial distribution network power flow and optimal reconfiguration based on improved BFS and ASTUNG techniques respectively. Azare distribution network was selected as a case study in order to carry out power flow and reconfiguration analysis. A GPS based technique is used to model the distribution network and to determine the most appropriate position of the tie switches required for network reconfiguration. 1.7 Methodology The following steps would be adopted in order to achieve the aim and objectives of this research work:
1. Obtaining the network topology of the Azare distribution network and propose optimum location of tie switches/branches (required for network reconfiguration) using GPS coordinate system;
2. Development of power flow and reconfiguration models and algorithms base on improved BFS and ASTUNG techniques for radial distribution network power flow and reconfiguration analysis respectively;
3. Design and programming of Graphic User Interfaces (GUIs) in MATLAB based on the developed power flow and reconfiguration algorithms to
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serve as tools for power flow and optimal reconfiguration analysis (simulators);
4. Performing power flow and optimal reconfiguration simulations on Azare distribution network using the developed GUIs and comparing the optimum and original configurations in terms of Real Power Loss, Voltage Profile, System Load Balancing Index (SLBI), Voltage Stability Index (VSI);
5. Validating the developed techniques using standard IEEE 30 and 33 bus radial distribution networks.
1.8 Significant Contributions This research work offers the following significant contributions to the existing body of knowledge:
1. Development of radial distribution network power flow and reconfiguration algorithms based on improved Backward-Forward Sweep (BFS) and All Spanning Trees of Undirected Network Graph (ASTUNG) techniques respectively. The developed algorithms introduce flexibility and decrease the complexity arising from large network simulation by breaking the solution strategy into a number of subsections (MATLAB function blocks) that works together to achieve the set objectives. .
2. MATLAB GUI based software packages (simulators) have been developed based on the developed power flow and reconfiguration algorithms. The developed simulators can easily be used to accurately
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perform power flow and reconfiguration analysis on either small or large distribution network.
3. The developed optimal reconfiguration simulator was able to improve the voltage profile of the simulated Azare distribution network by 64.11% and reduce its total real power loss by 54.4%. The simulator was also able to improve the voltage profile of the standard 33 buses IEEE radial network by 14.23% and reduce its total real power loss by 0.31% compared to the corresponding optimum values obtained in the work of Rao et al., 2011.
1.9 Thesis Organization
In chapter one, general background on distribution system is presented; followed by an overview of Azare distribution system. In chapter two, a concise review of the fundamental concepts and literatures regarding radial distribution network power flow and reconfiguration are presented. In chapter three, the proposed improved BFS and ASTUNG techniques and algorithms as applied to radial distribution network power flow and reconfiguration are presented respectively; Power flow and reconfiguration simulators (MATLAB GUIs) are also developed and presented in the chapter. In chapter four, Azare distribution network power flow and reconfiguration are simulated using the developed simulators (presented in chapter three); the results are presented and briefly discussed; and the developed simulators were further tested using IEEE standard 30 and 33 bus radial networks as a means of validation. Chapter five presents the conclusion, recommendations, and limitations of the entire research work
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