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Smart EA operators for effective service restoration of compensated distribution networks

机译:智能EA运营商可有效恢复有偿配电网络的服务

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An effective service restoration (SR) strategy for distribution network plays a key role in improving service reliability and enhancing customers' satisfaction. Several evolutionary algorithms (EAs) have been developed in order to solve this problem. However, most of them do not include compensators in the plan. Others use some simplifying assumptions in order to limit the search space, which degrade the quality of obtained results. In addition, EAs suffer from high computational burden especially when improper modeling and operators are used. This paper proposes a set of Smart operators for the EA in order to effectively solve the SR problem of compensated distribution networks in an integrated framework. The proposed operators improve the EA's performance by guiding the search to more productive areas of the search space using more information about status of the network. Simulations prove efficiency of the proposed method by providing fast and high quality results.
机译:有效的配电网络服务恢复(SR)策略在提高服务可靠性和提高客户满意度方面起着关键作用。为了解决这个问题,已经开发了几种进化算法(EA)。但是,它们中的大多数都没有在计划中包括补偿器。其他人则使用一些简化的假设来限制搜索空间,从而降低了获得结果的质量。此外,EA承受着很高的计算负担,尤其是在使用不正确的建模和运算符时。本文提出了一套针对EA的智能算子,以有效解决集成框架下有偿配电网的S​​R问题。拟议的运营商通过使用有关网络状态的更多信息将搜索引导到搜索空间中更高产的区域,从而提高EA的性能。仿真通过提供快速和高质量的结果证明了该方法的有效性。

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