A Two-stage Stochastic Optimization Approach for Distribution Network with Load Control

With the extensive access of distributed energy resources (DER) and the development of load control technology, the distribution network is gradually becoming more and more initiative, and the economy of power grid can be effectively improved through reasonable scheduling. For this purpose, a two-stage stochastic optimization approach for distribution network with load control is established. The scenario analysis is used to characterize the uncertainty of DER. The first stage of optimization generates a day-ahead power purchase curve and load adjustment curves and calculates the corresponding costs; In the second stage, the mathematic expectation of the difference between the actual purchased electricity in each scenario and the day-ahead purchased electricity is calculated to obtain the reserve costs. The mathematical nature of the model is a large-scale nonlinear mixed integer programming problem, which is difficult to solve. By using the second-order cone (SOC) relaxation technique, the above model can be transformed into a mixed integer second-order cone programming (MISOCP) form, which can be solved effectively. Finally, the simulation analysis of the custom IEEE 14-bus system is carried out to verify the effectiveness of the proposed model.