Multi-Objective Fault Recovery Model of Active Distribution Network Considering Randomness of Distributed Generation

In this paper, a multi-objective fault recovery model of active distribution network considering the randomness of distributed generation (DG) is proposed. This model aims to balance the maximization of load recovery, the minimization of switching operations and the economy and reliability of island operation. By introducing Gaussian mixture model (GMM) to model the randomness of DG, effective fault recovery can be achieved in different situations. Particle Swarm Optimization (PSO) is used to solve the model, which effectively balances multiple conflicting objectives. The case analysis shows that the model can maintain more than 80% load recovery ratio in different fault scenarios, significantly reduce the number of switching operations, and maintain a high load recovery ratio and island operation stability under DG output fluctuation. The research results provide an efficient and flexible strategy for fault recovery of active distribution network, and enhance the power supply reliability and fault response ability of the power grid.