Paper Info
Title
Comparative Study On The Application Of Modern Heuristic Techniques To Svc Placement Problem
Abstract
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.
Year
DOI
Venue
2009
10.4304/jcp.4.6.535-541
JOURNAL OF COMPUTERS
Keywords
Field
DocType
FACTS devices, SVC, Modern heuristic techniques, Evolutionary Programming, Genetic Algorithm, Particle Swarm Optimization, Evolutionary PSO
Particle swarm optimization,Mathematical optimization,Heuristic,Nonlinear system,Computer science,AC power,Evolutionary programming,Genetic algorithm
Journal
Volume
Issue
ISSN
4
6
1796-203X
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Mehdi Eghbal120.81
Naoto Yorino246.46
Yoshifumi Zoka323.86