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In order to consider the correlation between distributed power output and load, this paper uses the value-at-risk theory to quantitatively calculate the uncertainty of wind speed and load demand, and establishes a wind speed-load joint probability distribution model using bivariate normal distribution, which will take into account the wind speed uncertainty. The robust decision-making problem of reliability and load participation is characterized as a mixed-integer linear programming problem, which takes the minimization of the equivalent load loss as the optimization goal, establishes the load recovery path as the optimization variable, and takes the wind speed and load as the disturbance variable to account for the wind speed-The load-dependent robust restoration model of the distribution network is solved by the Gurobi high-efficiency solver. Finally, the IEEE69-bus power distribution system with wind power was used to verify the effectiveness of this model and solution method.

With the growing penetration rate of distributed generations (DGs) and large number of unordered charging electric vehicles (EVs), the distribution network (DN) is facing more challenges than before. Therefore, the DN planning integrated of EVs and DGs is the primely problem. Firstly, an traffic network model and a distributed power supply output model are established to simulate the actual traffic network flow distribution through the principle of user equilibrium flow distribution. Secondly, an improved adaptive free search algorithm is proposed to coordinate site selection planning of EV charging pile and DG considering the factors of economy and users’ satisfaction of charging. Finally, taking the modified IEEE 33-node distribution network as an example, the proposed model and algorithm are simulated and verified. The simulation results show that the proposed model and programming method are feasible and effective.