Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems
Publication: Research - peer-review › Journal article – Annual report year: 2009
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 language | English |
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| Journal | Expert Systems with Applications |
| Publication date | 2009 |
| Volume | 36 |
| Journal number | 8 |
| Pages | 10802-10808 |
| ISSN | 0957-4174 |
| DOIs | |
| State | Published |
| Citations | Web of Science® Times Cited: 6 |
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ID: 4133090