About this Journal Submit a Manuscript Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2011 (2011), Article ID 942672, 13 pages
http://dx.doi.org/10.1155/2011/942672
Research Article

Contingency-Constrained Optimal Power Flow Using Simplex-Based Chaotic-PSO Algorithm

Department of Electrical Engineering, Kao-Yuan University, Kaohsiung City 821, Taiwan

Received 26 September 2010; Revised 18 February 2011; Accepted 25 April 2011

Academic Editor: Chuan-Kang Ting

Copyright © 2011 Zwe-Lee Gaing and Chia-Hung Lin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper proposes solving contingency-constrained optimal power flow (CC-OPF) by a simplex-based chaotic particle swarm optimization (SCPSO). The associated objective of CC-OPF with the considered valve-point loading effects of generators is to minimize the total generation cost, to reduce transmission loss, and to improve the bus-voltage profile under normal or postcontingent states. The proposed SCPSO method, which involves the chaotic map and the downhill simplex search, can avoid the premature convergence of PSO and escape local minima. The effectiveness of the proposed method is demonstrated in two power systems with contingency constraints and compared with other stochastic techniques in terms of solution quality and convergence rate. The experimental results show that the SCPSO-based CC-OPF method has suitable mutation schemes, thus showing robustness and effectiveness in solving contingency-constrained OPF problems.