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An Encoding Technique for Multiobjective Evolutionary Algorithms Applied to Power Distribution System Reconfiguration

机译:用于配电系统重构的多目标进化算法编码技术

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摘要

Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal solutions during the reconfiguration of power distribution systems considering multiobjective optimization. The encoding scheme is based on the edge window decoder (EWD) technique, which was embedded in the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and the Nondominated Sorting Genetic Algorithm II (NSGA-II). The effectiveness of the encoding scheme was proved by solving a test problem for which the true Pareto-optimal solutions are known in advance. In order to prove the practicability of the encoding scheme, a real distribution system was used to find the near Pareto-optimal solutions for different objective functions to optimize.
机译:网络重新配置是减少功率损耗并优化配电系统运行的一种替代方法。本文提出了一种用于进化算法的编码方案,以便在考虑多目标优化的配电系统重构期间有效地搜索帕累托最优解。编码方案基于边缘窗口解码器(EWD)技术,该技术嵌入在强度帕累托进化算法2(SPEA2)和非支配排序遗传算法II(NSGA-II)中。通过解决一个测试问题证明了编码方案的有效性,对于该问题,事先知道了真正的帕累托最优解。为了证明该编码方案的实用性,使用了一个实际的分配系统来找到针对不同目标函数进行优化的近帕累托最优解。

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