الفهرس 
CHAPTER 1: INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The penetration of Distributed Generation sources (DGs), such as Fuel Cells (FCs), Photovoltaic (PV), solar-thermal, and Micro-Turbines (MTs) systems in electric distribution networks, is growing continuously. DGs are revolutionary approach that employs small-scale technologies to produce electricity close to the distribution network or as near as possible at center of loads (customers). So, the operation of electric power system will be changed by using these devices. DG technologies often consist of modular generators that can be powered by conventional and/or new and renewable energy sources. This thesis presents a review of DGs definition, classifications, economical and operational benefits, and the major issues that are raised in the DG literature to help in understanding the basics and concepts of implementing of DGs in the distribution network. One of the promised DGs is FC. This thesis introduces a survey of FCs technology (definition, structure, and theory of work). A general description of FC types is explained indicating application, development, advantages, drawbacks, and principal uses of each type. Also, economics of producing electricity from different types of new (FC) and renewable (wind and solar) energy are examined under different conditions and a comparison between most commonly used DGs (FCs, WT, and PV) is presented. After installing DGs, a low cost of electricity, reliability, higher power, and security with fewer environmental consequences may be provided. DGs are strategically located and operated in the distribution network to enhance voltage stability, improve voltage profile, reduce system losses, reinforce grid, and to improve system reliability and efficiency. Although DGs have in general positive effects, they sometimes cause voltage control problems by generation power disregarding distribution system conditions. So, optimal allocation selection of DGs in the distribution network is a very crucial aspect of energy system planning. Over the past few years, some powerful techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been developed to overcome most of the difficulties of conventional methods. This thesis presents an efficient and reliable evolutionary-based approach to solve the Optimal Power Flow (OPF) problem. The OPF is formulated as a nonlinear constrained objective optimization problem with both equality and inequality constraints. PSO is a proposed algorithm to solve the OPF problem. To illustrate the effectiveness of the proposed algorithm, the obtained results from the PSO are compared with another optimization technique, i.e. (GA). Three different objective functions are considered for the considered power systems to verify the effectiveness of the PSO algorithm. These objective functions are minimizing of ”fuel cost of generating units”, ”total active power loss”, and ”weighted multi-objective function”. Utilization of the proposed algorithm has been successfully applied with two different test power systems; the first one is the standard IEEE 30-bus test power system and the second is the West Delta Network (WDN) 52-bus system. Also, the optimal allocation of DGs using different optimization techniques will be presented. The results show the effectiveness of the proposed PSO with optimal allocation of DGs compared with another optimization technique, i.e. (GA), in term of reduced active power loss. These studies introduce an analysis of voltage and reactive power control as well as voltage stability margins in electric distribution system whether DGs are present or not. Also, the optimal allocation of shunt capacitor banks using PSO technique will be
presented to minimize active power loss, improve the overall voltage profile, and decrease voltage deviation of the load buses. Power World Simulator (PWS) is a simple tool that can be used in allocating DGs on the primary distribution networks for maximum revenue, continuity of service, and voltage stability enhancement as well as relieving overloading on feeders. PWS and PSO are handled to solve the problem as an optimization problem with mild constraints. The considered objective functions are minimizing distribution real power losses and Network Security Index (NSI) and maximizing Voltage Stability Factor (VSF). The software (PWS) has been tested on a typical radial 15-bus distribution system. Also, the optimal allocation of DGs in primary distributed networks using software (PWS) is presented and compared with the results from PSO to ensure capability and simplicity of the proposed solution.