Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
387835 | Expert Systems with Applications | 2009 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
John G. Vlachogiannis, Kwang Y. Lee,