摘要
为了解决大规模电力系统的无功优化问题，提出一种新型的退火选择遗传算法及其改进算法。大量数字例的统计分析结果表明，与简单遗传算法相比，这两类算法收敛速度快，逃脱局部极值能力强，而且系统规模越大这种优越性越明显。该算法具有通用性，能用于其他系统优化问题。
In this paper a new genetic algorithm with annealing selection (AGA) and its improvement (MAGA) are proposed to optimize the VAR distribution in large scale power systems.Massive statistics and analysis show that these algorithms are superior to the simple genetic algorithm (SGA) in convergence and ability to escape local optimums,especially in large scale problems.The algorithms are quite generic and can be applied to other system optimization problems.
出处
《中国电力》
CSCD
北大核心
1998年第2期3-6,共4页
Electric Power
基金
国家教委博士点基金
关键词
遗传算法
模拟退火
电力系统
无功功率
genetic algorithms (GA) VAR optimization simulated annealing
