首页> 外文会议>Proceedings of the 44th Hawaii International Conference on System Sciences >An Evolved Skeleton-Network Reconfiguration Strategy Based on Topological Characteristic of Complex Networks for Power System Restoration
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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征的演化骨架网络重构策略

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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:大规模停电后恢复电力系统是电力系统安全的关键问题。重建合理的骨架网络是建立主网络并快速恢复负载的有效方法。根据复杂网络的拓扑特征,提出了一种演化的骨架网络重构策略。进化策略利用线间性以及节点重要度和聚类系数,完善了称为网络重配置效率的指标,该指标旨在选择关键节点和关键线进入目标网络,同时保持其稀疏性,以减轻重配置的负担。然后,将离散粒子群算法用于实现进化策略。在IEEE 57总线电源系统上的应用验证了从演进的策略派生而来的骨架网络不仅包括所有关键节点,而且还包括大多数关键线路,从而突出了重新配置的主要任务。

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