With the development of science and technology

multiple important issues are faced in the active distribution network. Firstly

with the access of a large number of flexible loads and electric vehicles the type of loads shows obvious diversification and the complexity of the grid management is increased. Secondly

the randomness and fluctuation of renewable energy sources present significant challenges to the grid fault recovery. To deal with these issues

a fault recovery strategy for the active distribution network concerning diverse energy interactions is proposed. This strategy sets up an optimization with the maximizing controllable distributed generation actions and minimizing power loss as the goal and

at the same time

system security constraints are met. For solving the model

an improved binary particle swarm optimization algorithm and genetic algorithm are used. The experimental result shows through simulation analysis on the IEEE33 node distribution model that the strategy can not only effectively reduce the grid loss and recover the power loss to the greatest extent

but also provide a kind of potential solution for the grid management to the challenge of renewable energy and multiple loads.