Universiti Teknologi Malaysia Institutional Repository

Optimal placement of static VAR compensator using genetic algorithms

Mustafa, Mohd. Wazir and Wong, Yan Chiew (2008) Optimal placement of static VAR compensator using genetic algorithms. Elektrika, 10 (1). pp. 26-31. ISSN 0128-4428

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Official URL: http://www.fke.utm.my/elektrika/june08/paper5june0...


The management of power systems has become more difficult than earlier because power systems are operated closer to security limits, environmental constraints restrict the expansion of transmission network and the need for long distance power transfers has increased. The loading of a transmission network can be increased by maintaining proper voltage profile through injecting appropriate reactive power into the system. The existence of the multiple solutions in the optimal placement of reactive power in the power system typically often get stuck at the local optimum rather than at the global optimum. Genetic Algorithms (GAs) are stochastic searching algorithms that make the searching process jumps randomly from point to point, thus allowing escape from the local optimum, and search for many sub-optimum points in parallel.This paper presents an evolutionary computation algorithm for enhancing voltage stability. GAs will determine the most vulnerable bus in the power system, where the Static VAR Compensator (SVC) is needed to be installed at that bus as well as considering installation cost of SVC. The developed algorithms have successfully obtained the best solution for optimal placement of SVC in the IEEE 9 buses system and TNB northern area 275kV 14-bus system

Item Type:Article
Uncontrolled Keywords:genetic algorithms, optimization, static VAR compensator, piwer generation, Tenaga Nasional Berhad
Subjects:T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:9932
Deposited By: Siti Najwa Hanim Kamarulzaman
Deposited On:22 Jun 2010 08:24
Last Modified:11 May 2011 04:34

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