Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. The locations of controllers are determined based on two considerations which are increment of distance to collapse point and minimizing real power loss of system. The Static Var Co...

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Bibliographic Details
Main Author: Karami, Mahdi
Format: Thesis
Language:English
Published: 2011
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/41680/1/FK%202011%20130R.pdf
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Summary:This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. The locations of controllers are determined based on two considerations which are increment of distance to collapse point and minimizing real power loss of system. The Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) are used in this thesis. These controllers can be connected in series, shunt or combination of both with the system. This study is focused on placement of mentioned FACTS devices in power system network which are the famous types of these controllers while most of works had been done with regards to one or limited types of FACTS controllers. The basic structure of FACTS devices and their configuration is described. A heuristic method known as genetic algorithm is used to seek the optimum location and setting of these controllers where there are some works related to this case using various techniques. The genetic algorithm technique is explained and the real number representation of genetic algorithm is modeled. Most of the previous close studies have been performed to optimize two parameters i.e. location and rated value of each device only, while all the possible control parameters of each device including its location are optimized simultaneously in this study. The IEEE 14-bus, 57-bus and 118-bus test systems are utilized during this research to verify the recommended method. The modeling of power systems, FACTS devices and genetic algorithms are performed through MATLAB/PSAT simulation. The power flow analysis and continuation power flow analysis are employed to verify the performance of systems and to determine the collapse point of systems respectively. The results achieved from the simulations manifestly proved that the proposed method is an effective approach for placement of various types of FACTS controllers considering different problems in power system.