配电系统重构与电容器配置的多目标优化

D. P. Montoya, J. M. Ramirez, J. R. Zuluaga
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引用次数: 5

摘要

本文提出了一种结合最小生成树(MST)的多目标优化方法来并行解决电容器最优分配的重构问题。该方法基于遗传算法和Kruskal算法的结合。重新配置问题通过MST解决,嵌入到NSGA-II中以解决总体问题。合适的适应度函数的选择提供了一种能够减少功率损耗和改善配电网电压分布的解决方案。为了解决这一问题,提出了一种基于年节电最大化、总功率损耗最小化和总电压偏差最小化的多目标公式。在测试系统上进行的对比测试证明了该算法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-objective optimization for reconfiguration and capacitor allocation in distribution systems
This paper proposes a multi-objective optimization in conjunction with a minimal spanning tree (MST) to solve the reconfiguration problem in parallel with the optimal capacitor allocation. The proposed method is based on a combination of genetic algorithm and the Kruskal Algorithm. The reconfiguration problem is solved through the MST, embedded into a NSGA-II for solving the total problem. An appropriate selection of the fitness functions provides a solution that is able to reduce power loss and improve the voltage profile in the distribution network. To solve the problems, a multi-objective formulation based maximization of the annual savings, minimization of total power loss, and minimization of total voltage deviation on the buses is proposed. The comparative test performed on test systems has demonstrated the accuracy of the proposed algorithm.
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