An intelligent decision-making model of network reconfiguration for power system restoration

This paper develops an intelligent decision-making model for network reconfiguration during power system restoration. The goal of the proposed model is to find the shortest restored weighted energized paths for units start-up or load recovery, and a weight coefficient is introduced to comprehensively asses the power line to be energized. The Data Envelopment Analysis (DEA) method with preference information is employed in this paper to implement the evaluation of the weight coefficient with respect to power line. Finally, the IEEE 30-bus standard system is employed to illustrate the effectiveness of the proposed evaluation method.