Active and Reactive Power Scheduling of Distribution System Based on Two-Stage Stochastic Optimization

With the large-scale integration of distributed resources into the distribution network, such as wind/solar power and electric vehicles (EVs), the uncertainties have rapidly increased in the operation optimization of the distribution network. In this context, it is of great practical interest to ensure the security and economic operation of the distribution network. This paper addresses this issue and makes the following contributions. Firstly, a two-stage stochastic rolling optimization framework for active–reactive power scheduling is established. In the first stage, it dispatches the active power of distributed resources. In the second stage, it optimizes the reactive power compensation based on the first-stage scheduling plan. Secondly, the simulation-based Rollout method is proposed to obtain the improved active power dispatching policy for cost optimization in the first stage. Meanwhile, the aggregated power of EVs can be determined based on the mobility and charging demand of EVs. Thirdly, based on the aggregated power of EVs, a scenario-based second-order cone programming is applied to perform the rolling optimization of reactive power compensation for voltage performance improvement in the second stage. The numerical results demonstrate that this method can effectively improve the economic operation of the distribution network while enhancing its operational security by leveraging the charging elasticity of EVs.