收稿日期: 2009-06-26
修回日期: 2009-10-16
网络出版日期: 2010-03-25
基金资助
国家自然科学基金资助项目(B05-B5070310)
Improved Catastrophic Genetic Algorithm and Its Application to Reactive Power Optimization
Received date: 2009-06-26
Revised date: 2009-10-16
Online published: 2010-03-25
Supported by
国家自然科学基金资助项目(B05-B5070310)
蒋金良 林广明 欧阳森 曾江 . 改进灾变遗传算法及其在无功优化中的应用[J]. 华南理工大学学报(自然科学版), 2010 , 38(3) : 95 -100 . DOI: 10.3969/j.issn.1000-565X.2010.03.017
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
[1]null
/
| 〈 |
|
〉 |