Contingency-Constrained Optimal Power Flow Using Simplex-Based Chaotic-PSO Algorithm. (18th July 2011)

• Record Type: Journal Article
• Authors: Gaing, Zwe-Lee; Lin, Chia-Hung
• Other Names: Ting Chuan-Kang Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2011(2011)
• Publication Date: 2011-07-18
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2011/942672
• Languages: English
• ISSNs: 1687-9724

Abstract

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.