To improve the accurate prediction of electric vehicle (EV) charging load and ensure the stability and economy of the distribution network penetrated with a large scale of EV is one of the key issues in realizing a win-win situation for the EV and distribution network. In this paper, a combined optimization model of active and reactive power for active distribution network reconstruction and its solution method are established considering the characteristics of EV temporal and spatial load distribution. First, from travel chain technology and Markov decision theory, and considering the influence of weather, the EV owner and traffic, an EV unit energy consumption model and the spatial-temporal load model of charging load are constructed. Secondly, considering all of the energy storage system, on-load tap changer, capacitor banks, static var compensation, dynamic reconfiguration of various active management measures, economic indicators and operation constraints, a dynamic reconfiguration and active reactive-power optimization model of an EV active distribution network are established. Then, to improve solution efficiency, the original model is transformed into a mixed integer second order cone model using second-order cone relaxation and variable product linearization methods. Finally, an improved IEEE33 system is used for simulation analysis to verify the effectiveness and superiority of the proposed method. This work is supported by the National Natural Science Foundation of China (No. 52107108).