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An Evolved Skeleton-Network Reconfiguration Strategy Based on Topological Characteristic of Complex Networks for Power System Restoration

机译:基于复杂网络拓扑特性的电力系统恢复的拓扑特性发展的演变骨架网络重配置策略

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The restoration of a power system following large-scale blackouts is a key issue to the safety of power systems. Reconstructing the reasonable skeleton-network is an effective means of establishing the main network and restoring loads quickly. Based on the topological characteristic of complex networks, an evolved skeleton-network reconfiguration strategy is proposed in this paper. Employing line betweenness as well as node importance degree and clustering coefficient, the evolved strategy refines the index named network reconfiguration efficiency, which aims to select key nodes and key lines into the target network while keeping its sparseness in order to alleviate the burden of reconfiguration. Then, discrete particle swarm optimization is used in realizing the evolved strategy. Application to the IEEE 57-bus power system verifies that skeleton network derived from the evolved strategy includes not only all critical nodes but also most critical lines thereby highlighting the main task of reconfiguration.
机译:大规模停电后电力系统的恢复是电力系统安全的关键问题。重建合理的骨架网络是一种有效的方法,可以快速建立主网络并恢复负载。基于复杂网络的拓扑特性,本文提出了一种进化的骨架网络重新配置策略。在与节点之间的内容和节点之间使用线路,进化策略会改进名为网络重新配置效率的索引,这旨在选择关键节点和键入目标网络的同时保持其稀疏,以便缓解重新配置的负担。然后,离散粒子群优化用于实现进化的策略。应用于IEEE 57总线电力系统验证从演进策略导出的骨架网络不仅包括所有关键节点,而且还包括最关键的线条,从而突出了重新配置的主要任务。

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