Disaster Prediction-based Resilience Enhancement Strategy for Multi-hour Power Supply in Distribution Networks

Considering the extreme disaster risk faced by the distribution network, a disaster prediction-based resilience enhancement power supply strategy for the distribution network was proposed. Firstly, the effect of disaster prediction on improving the flexible power supply of the distribution network was analyzed. Secondly, considering the optimal deployment of emergency power vehicles and the transfer of electric energy, a three-stage power supply elasticity improvement model for distribution network disaster prevention, resistance, and recovery was proposed based on the disaster prediction information. Thirdly, the constructed non-convex nonlinear model was transformed into a mixed integer second-order cone programming model and solved by using the second-order cone relaxation method. Finally, the effectiveness and superiority of the proposed strategy are verified through the example simulation of the improved 69-node power distribution system.