关键词：
改进自适应遗传算法;分布式发电;多目标优化;模糊优化;配电网规划
摘 要：
针对遗传算法在进行多目标优化时,收敛速度慢且易早熟的问题,提出一种改进自适应遗传算法,改进了选择方法和终止判据,并对交叉和变异概率的选取进行了自适应处理。针对含分布式发电的配电网规划的多目标性,采用模糊理论引入总体满意度很好地解决了多目标归一化问题。仿真算例表明:改进的算法能有效地寻找到全局最优解,明显提高收敛速度,具有良好的自适应特性。
译 名：
Optimal Algorithm on Distribution Network Planning Including Distributed Generation
作 者：
ZHANG Yun,WANG Yan-jun(College of Electrical and Mechanical,Hebei Agricultural University,Baoding Hebei 071001,China)
关键词：
improved self-adaptive genetic algorithm;distributed generation;multi-objective optimization;fuzzy optimization;distribution network planning
摘 要：
The genetic algorithm has some defects for optimizing multi-objectives,such as slow convergent speed and easily premature.An improved self-adaptive genetic algorithm was proposed,for improving terminational criterion and method of selection,making a self-adaptive disposal in crossover and mutation probability.Considering multi-objectives of distribution network planning including distributed generation,this article introduced totally satisfied degree by employing the fuzzy optimal theory,which was a good way to transform multi-objectives into single objective.Results of a system simulation showed that this algorithm could seek the best result of overall situation effectively,increase the convergence speed obviously,and had favorable self-adaptive characteristics.
