Improved Techniques for Sizing and Allocation of Distributed Generators in Electrical Systems Using Voltage Stability Indices: A Thesis for the Degree . In Electrical and Control Engineering

Salem, Eng Salma Sayed

ISBN 13: 9798635953334

Published by Independently published, 2020

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Bibliographic Details

• Title: Improved Techniques for Sizing and Allocation of Distributed Generators in Electrical Systems Using Voltage Stability Indices: A Thesis for the Degree . In Electrical and Control Engineering
• Publisher: Independently published
• Publication Date: 2020
• Language: English
• ISBN 13: 9798635953334
• Binding: Soft cover
• Condition: New

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Synopsis

Recently, the expansion of energy demand is increasing rapidly so, it is very important to operate the power flow at its maximum capacity. One possible solution to attenuate the capacity problem of the network is to encourage the wide use of Distributed Generators (DGs). Some positive support benefits of DG installation are system energy loss reduction, voltage profile augmentation, reliability improvement, lower operating cost and flexibility to install in terms of investment and time. Yet, the network parameters such as network stability and network power losses are affected by the increasing in DG units. Consequently, optimal distributed generation placement (ODGP) provides the best locations and sizes of DGs in order to optimize the operation of the electrical network.The present work is aimed to; estimate the locations and sizes of DG units to be integrated within the network. This estimation has been inspected taking into account voltage stability enhancement and active power losses minimization. The well-known General Algebraic Modeling System (GAMS) was used to optimize the objective functions considering the operating constraints. The results were compared to those obtained from artificial intelligent techniques namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The purpose of this thesis is to first, determine the location of the DG unit i.e. the weakest bus, through the voltage stability indices, and second to select the suitable size of the DG unit utilizing two different artificial intelligent techniques. To achieve these goals, the proposed network model and various objective functions with many operating constraints were studied and simulated. The system under study is considered as the IEEE 14 bus modified test network.