ISSN : 1796-203X
Volume : 4    Issue : 6    Date : June 2009

Comparative Study on the Application of Modern Heuristic Techniques to SVC Placement Problem
Mehdi Eghbal, Naoto Yorino, and Yoshifumi Zoka
Page(s): 535-541
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This paper investigates the applicability and effectiveness of modern heuristic techniques for solving
SVC placement problem. Specifically, Genetic Algorithm (GA), Particle Swarm Optimization (PSO)
and Evolutionary PSO (EPSO) have been developed and successfully applied to find the optimal
placement of SVC devices. The main objective of the proposed problem is to find the optimal
number and sizes of the SVC devices to be installed in order to enhance the load margin when
contingencies happen. SVC installation cost and load margin deviation are subject to be minimized.
The proposed approaches have been successfully tested on IEEE 14 and 57 buses systems and a
comparative study is illustrated. To evaluate the capability of the proposed techniques to solve large
scale problems, they are also applied to a large scale mixed-integer nonlinear reactive power
planning problem. Results of the application to IEEE 14 bus test system prove the feasibility of the
proposed approaches and outperformance of PSO based techniques over GA.

Index Terms
FACTS devices, SVC, Modern heuristic techniques, Evolutionary Programming, Genetic Algorithm,
Particle Swarm Optimization, Evolutionary PSO