Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (3): 95-100.doi: 10.3969/j.issn.1000-565X.2010.03.017

• Power & Electrical Engineering • Previous Articles     Next Articles

Improved Catastrophic Genetic Algorithm and Its Application to Reactive Power Optimization

Jiang Jin-liang  Lin Guang-ming  Ouyang Sen  Zeng Jiang   

  1. School of Electric Power, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2009-06-26 Revised:2009-10-16 Online:2010-03-25 Published:2010-03-25
  • Contact: 蒋金良（1953-），男，副研究员，主要从事电力市场和电力企业管理研究． E-mail:jljiang@seut．edu．cn
  • About author:蒋金良（1953-），男，副研究员，主要从事电力市场和电力企业管理研究．
  • Supported by:

    国家自然科学基金资助项目（B05-B5070310）

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Abstract:

In order to resolve the issues of prematurity and instability of catastrophic genetic algorithm （CGA）, an improved CGA （ICGA） is proposed, and an improved catastrophic operator related to the generation number is de- signed. Moreover, considering both the global performance and the convergence speed, two probability algorithms respectively for the crossover related to the generation number and for the mutation related to the fitness are de- signed. The proposed ICGA is finally applied to the reactive power optimization of the IEEE 14-bus and the IEEE 30-bus systems. The results show that ICGA is applicable to the reactive power optimization of power system due to its good global performance and high convergence speed.

Key words: genetic algorithm, catastrophe, reactive power optimization

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