Applications of Particle Swarm Optimization in Composite Power System Reliability Evaluation

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Author(s): Mohammed A. Benidris (Michigan State University, USA), Salem Elsaiah (Michigan State University, USA)and Joydeep Mitra (Michigan State University, USA)
Copyright: 2015
Pages: 38
Source title: Handbook of Research on Swarm Intelligence in Engineering
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)and Paramartha Dutta (Visva-Bharati University, India)
DOI: 10.4018/978-1-4666-8291-7.ch018

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science / Engineering Science Reference

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Abstract

This chapter introduces a novel technique to evaluate composite power system reliability indices and their sensitivities with respect to the control parameters using a dynamically directed binary Particle Swarm Optimization (PSO) search method. A key point in using PSO in power system reliability evaluation lies in selecting the weighting factors associated with the objective function. In this context, the work presented here proposes a solution method to adjust such weighting factors in a dynamic fashion so that the swarm would always fly on the entire search space rather of being trapped to one corner of the search space. Further, a heuristic technique based on maximum capacity flow of the transmission lines is used in classifying the state space into failure, success, and unclassified subspaces. The failure states in the unclassified subspace can be discovered using binary PSO technique. The effectiveness of the proposed method has been demonstrated on the IEEE RTS.

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Applications of Particle Swarm Optimization in Composite Power System Reliability Evaluation

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