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Crowded comparison operators for constraints handling in NSGA-Ⅱ for optimal design of the compensation system in electrical distribution networks

机译:拥挤比较算子用于NSGA-Ⅱ中的约束处理,以优化配电网补偿系统

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This paper proposes an improvement of an efficient multiobjective optimization algorithm, Non-dominated Sorting Genetic Algorithm Ⅱ, NSGA-Ⅱ, that has been here applied to solve the problem of optimal capacitors placement in distribution systems. The studied improvement involves the Crowded Comparison Operator and modifies it in order to handle several constraints. The problem of optimal location and sizing of capacitor banks for losses reduction and voltage profile flattening in medium voltage (MV) automated distribution systems is a difficult combinatorial constrained optimization problem which is deeply studied in literature. In this paper, the efficiency of the proposed Crowded Comparison Operator, CCO1, is compared to the efficiency of another Crowded Comparison Operator, CCO2, whose definition derives from the constraint-domination principle proposed by Deb et al. The two operators are tested on difficult test problems as well as on the optimal capacitors placement problem.
机译:本文提出了一种有效的多目标优化算法,即非支配排序遗传算法Ⅱ,NSGA-Ⅱ的改进方法,该算法已被用于解决配电系统中电容器的最优布置问题。研究的改进涉及拥挤比较运算符,并对它进行修改以便处理一些约束。在中压(MV)自动配电系统中,用于降低损耗和电压分布平坦化的电容器组的最佳位置和尺寸问题是一个难以解决的组合约束优化问题,已有文献对此进行了深入研究。在本文中,将拟议的拥挤比较算子CCO1的效率与另一个拥挤比较算子CCO2的效率进行比较,后者的定义源自Deb等人提出的约束支配原理。对这两个操作员进行了艰难的测试问题以及最佳电容器放置问题的测试。

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