To improve the overall efficiency of the power system, the performance of transmission system must be improved. Some of the vital ways of achieving this objective is by reducing power losses in the system and also improving voltage profile. An important method of controlling bus voltage is by shunt capacitor banks in the transmission substations. The capacitor absorbs reactive power flow in the system, thus improving power factor. When this is done, active power is also improved. In this work, a 10-bus transmission system is taken as model. Newton-Raphson’s power flow program is executed using MATLAB toolbox to obtain p. u nodal voltage ranging from 0.8890 to 1.0564, total real power line losses (0.09438 p.u), and total reactive power line losses (0.36970 p. u). By using power loss reduction, power loss index is evaluated and normalized in the range [0, 1]. These indices, together with the p. u nodal voltage magnitude, is fed as inputs to the Fuzzy Inference System to obtain Capacitor Suitability Index (CSI). The CSIs obtained, ranges from 0.244 to 0.897. The values of the CSIs determine nodes most suitable for capacitor installation. Experimentally, highest values of CSIs are chosen for capacitor installation. As a result, 3 buses (3, 8, and 10) with CSI values of 0.680, 0.750, and 0.897 respectively, are chosen. Capacitor sizes of 50MVar, 85MVar, and 60MVar (obtained from Index Based Method) are installed on the buses. Voltage profile improves by 3.74%, 3.27%, and 3.33% respectively, while total real power loss in the system reduces by 17.55% and total reactive power injection to the network reduces by 8.70% respectively. Overall, system stability and efficiency, hence, reliability, are improved by installation of capacitors at suitable locations in a transmission system.

CHAPTER ONE

INTRODUCTION

1.1 Background of Study

Electrical energy is generated at power stations which are usually located far away from load centres [1]. Thus, a network of conductors between the power stations and the consumers is required in order to harness the power generated. This network of conductors may be divided into two main components, namely, the transmission system and the distribution system [1]. As power flows in the lines, a significant amount is lost. Accurate knowledge of these power losses on transmission lines and their minimization is a critical component for efficient flow of power in an electrical network. Power losses result in lower power availability to final consumers. Hence, adequate measures need to be taken to reduce power losses to the barest minimum.

Power plants' planning in a way to meet the power network load demand is one of the most important and essential issues in power systems. Since transmission lines connect generating plants and substations in power network, the analysis, computation and reduction of transmission losses in these networks are of great concern to scientists and engineers.

1.5 Scope of the Study

The scope of this work is limited to a 10-bus model transmission network. The bus system (which cut across 2 of the 8 TCN regions), is carefully chosen as a case study for this work. This is because of higher losses and voltage drops experienced in the regions. Power flow analysis of this sub-network is conducted to obtain losses. ‘Capacitor placement method’ is applied using Fuzzy logic technique to determine the sizes and locations of buses to install the capacitors. Sizes of capacitors to be installed are equally evaluated.

1.6 Organization of Thesis

This work is organized in five chapters. Chapter one presents a general introduction of the work. Chapter two presents an overview of power systems, power losses (both technical and non-technical), fuzzy logic technique, power flow analysis etc. Chapter three deals with the modeling of the selected 10-bus system, capacitor placement method, algorithm of the proposed approach, calculation of loss reduction & loss indices, calculation of capacitor sizes using Index Based method etc. Chapter four present fuzzy logic as simulation software used. Various results obtained from load flow analysis, fuzzy logic implementation, calculation of capacitor sizes and improvement recorded in voltage profile and reduction in total power losses were also presented and discussed in this chapter. Conclusion is drawn and necessary recommendation made in chapter five