The disorder of electric vehicles charging process in space will greatly influence the distribution network reconfiguration. On the premise of tending to choose the station of shortest distance and least time for users, a multi-objective optimization model considering space allocation of electric vehicles was established in this context. This model chose network loss and voltage deviation level as optimization goal with utility degree of the electric vehicles as constraint condition to optimize the network switch state and electric vehicles charging load space allocation at the same time. The fuzzy c-means clustering was adapted to cluster electric vehicles in the system according to the spatial index, reducing the dimension of the model effectively. Finally, the model is solved by the improved genetic algorithm to obtain an integrated optimization scheme. The simulation results show that the fuzzy c-means clustering can significantly reduce calculation difficulty and improve the convergence rate of the algorithm, besides, with the guidance of the reconstructed model, the grid ensured its operation economy and reliability, reducing the electric vehicle charging time and distance, proving the validity of the model and method.
