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

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.