基于布谷鸟搜索算法的径向配电网DG优化分配与规模

M. Majidi, A. Ozdemir, O. Ceylan
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引用次数: 16

摘要

现代智能电网的实现在操作控制方面带来了几个优势。负荷中心附近的分布式发电和存储设施可能是用于提高所消耗能源质量和可靠性的最重要的概念。传统的径向电力系统最初是为单向潮流而设计的,在配电系统中,分布式发电机组的选址和规模可能会给配电系统带来一些问题。本文提出了一种考虑全年负荷变化的传统配电网DG最优分配和调度方法。优化的目标是最小化一天的总电压变化TVV和馈线分支的每日能量损失百分比。首先将这两个目标表述为单个优化问题,然后将其合并为一个多优化问题。采用元启发式布谷鸟搜索算法求解约束优化问题。将该方法应用于一个12总线径向配电系统,并通过MATLAB仿真验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal DG allocation and sizing in radial distribution networks by Cuckoo search algorithm
Modern smart grid implementations bring several advantages in terms of operational controls. Distributed generation and storage facilities near the load centers are probably the most important concepts that are used to improve the quality and the reliability of the consumed energy. Siting and sizing of DG generations in distribution systems may create several problems in traditional radial power systems, which were originally designed for unidirectional power flows. This paper presents an optimal DG allocation and sizing approach in a traditional distribution network where the whole year load variation is taken into account. Optimization aims to minimize both the total voltage variation, TVV, in a day and daily percentage energy losses along the feeder branches. The two objectives are first formulated as singular optimization problems and then combined in a multi-optimization problem. Meta-heuristic Cuckoo search algorithm is used to solve the resulting constrained optimization problem. The proposed formulation is applied to a 12-bus radial distribution system and the MATLAB simulations are performed to validate the performance of the approach.
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