Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

Ioannis (John) Vlachogiannis, K Y Lee

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In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem of steady-state of power systems. Specifically, reactive power control is formulated as a multi-objective optimization problem and solved using the parallel VEPSO algorithm. The results on the IEEE 30-bus test system are compared with those given by another multi-objective evolutionary technique demonstrating the advantage of parallel VEPSO. The parallel VEPSO is also tested on a larger power system this with 136 busses. (C) 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
JournalExpert Systems with Applications
Issue number8
Pages (from-to)10802-10808
Publication statusPublished - 2009

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