Distribution Network Reconfiguration Using Augmented Grey Wolf Optimization Algorithm for Power Loss Minimization

Hanan Hamour, S. Kamel, L. Nasrat, Juan Yu
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引用次数: 14

Abstract

This paper proposes augmented Grey wolf optimizer (AGWO) for solving the radial distribution network reconfiguration problem. In the developed algorithm, the optimal switches combination is determined to change the topological structure of the system and reduce the total real power losses subject to the system operating constraints. AGWO inspired from behavior of the alpha α, and beta β grey wolves in the nature. The proposed algorithm is tested on IEEE 33-bus radial distribution system. The simulation results prove reasonable computing time and high performance of the proposed method comparing with other well-known optimization techniques.
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基于增强型灰狼优化算法的配电网络重构
针对径向配电网重构问题,提出了增强型灰狼优化算法。该算法在满足系统运行约束的前提下,确定最优开关组合,改变系统拓扑结构,降低实际总功耗。AGWO的灵感来自于自然界中α和β灰狼的行为。该算法在IEEE 33总线径向配电系统上进行了测试。仿真结果表明,与其他已知的优化技术相比,该方法具有合理的计算时间和较高的性能。
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