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文章摘要
基于模糊自适应模拟退火遗传算法的配电网故障定位
Fault location of distribution networks based on fuzzy adaptive simulated annealing genetic algorithm
Received:May 09, 2015  Revised:September 11, 2015
DOI:
中文关键词: 配电网  故障定位  模糊推理  模拟退火  自适应  遗传算法
英文关键词: distribution network, fault location  fuzzy inference, simulated annealing, adaptive, genetic algorithm
基金项目:
Author NameAffiliationE-mail
Xu Mi* College of Electrical Engineering,Shandong University sunxmjy@163.com 
Sun Ying College of Electrical Engineering,Shandong University  
Li Kejun College of Electrical Engineering,Shandong University  
Xiao Wenwen College of Electrical Engineering,Shandong University  
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中文摘要:
      配电网故障定位系统的不足与遗传算法易早熟、收敛速度慢等问题,结合模糊推理和自适应模拟退火遗传算法,提出一种模糊自适应模拟退火遗传算法(FASAGA)。该算法对评价函数做了容错性改进,在遗传选择时采用自适应机制与最佳个体保留策略,并结合模糊推理与自适应机制求取模糊自适应交叉算子、模糊自适应变异算子,引入模拟退火算法提高收敛速度与局部搜索能力。仿真结果说明该算法应用在配电网故障定位中的准确性、快速性与高容错性。
英文摘要:
      Due to the shortcomings of fault location system of distribution networks and the problems of genetic algorithm that it is prone to premature convergence and its convergence speed is slow, this paper proposes a fuzzy adaptive simulated annealing genetic algorithm (FASAGA) by integrating fuzzy inference and adaptive simulated annealing genetic algorithm. This algorithm improves fault tolerance of the fitness function, adopts the adaptive strategy and the optimal individual reserve strategy in genetic selection, calculates fuzzy adaptive crossover operator and fuzzy adaptive mutation operator by combining fuzzy inference and adaptive strategy, and adopts simulated annealing algorithm to improve convergence speed and local search ability. The accuracy, effectiveness and tolerant performance of this algorithm applied to the fault location of distribution networks are verified by simulation results.
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