一种新的模糊自适应模拟退火遗传算法在配电网重构中的应用  

A new fuzzy-based adaptive simulated annealing genetic algorithm in distribution network reconfiguration

作　　者：姜瀚书[1] 梁峰[1] 贾彦兵[1] 

机构地区：[1]东北电力大学 电气工程学院,吉林吉林132012

出　　处：《东北电力大学学报》2010年第4期53-57,共5页Journal of Northeast Electric Power University

摘　　要：本文对配电网的重构问题进行了研究,提出了结合实际的配电网重构目标函数,并将遗传算法引入其中,用来解决这个复杂的,多目标,多约束的组合优化问题。针对遗传算法收敛速度慢、容易"早熟"等缺点,结合模糊推理、模拟退火算法和自适应机制,采用一种改进的遗传算法——模糊自适应模拟退火遗传算法(FASAGA),实例分析表明,该算法比标准的遗传算法(SGA)具有更快的收敛速度和寻优效果。This reconstruction of the distribution network conducted a study, made light of the actual objective function of distribution network reconfiguration, and in which genetic algorithm is used to solve this complex, multi-objective, multi-constraint combinatorial optimization problem. Slow convergence of genetic algorithms, easy to ＂premature＂ and other shortcomings, combined with fuzzy reasoning, simulated annealing algorithm and adaptive mechanism, an improved genetic algorithm-Fuzzy Adaptive simulated annealing genetic algorithm （FASAGA）, case analysis shows that The algorithm than the standard genetic algorithm （SGA） has a faster convergence speed and optimization results.

关 键 词：配电网重构 遗传算法 模糊控制 模拟退火 自适应 

分 类 号：TM726[电气工程—电力系统及自动化]