Title :
Combining Strategy of Genetic Algorithm and Particle Swarm Algorithm for Reactive Power Optimization
Author :
Lu, Jingui ; Zhang, Li ; Yang, Hong
Author_Institution :
CAD Center, Nanjing Univ. of Technol., Nanjing, China
Abstract :
This paper is involved in reactive power optimization. The combining strategy of genetic algorithm and particle swarm algorithm is proposed for the optimization problem of reactive power in this paper. It is necessary that the initial individuals are feasible ones, and good individuals are chosen as the initial particles in the combining strategy. The numerical examples of IEEE-6 and IEEE-30 power systems for the combining strategy are performed for the reactive power optimization. The effectiveness of the combining strategy proposed in this paper has been demonstrated preliminarily from the examples.
Keywords :
genetic algorithms; particle swarm optimisation; reactive power; IEEE-30 power system; IEEE-6 power system; genetic algorithm; particle swarm algorithm; reactive power optimization; Gallium; Generators; Load flow; Optimization; Particle swarm optimization; Reactive power; garticle swarm optimization algorithm; genetic algorithm; reactive power optimization;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.882