A Multi-Stage Optimization Approach for Active Distribution Network Scheduling Considering Coordinated Electrical Vehicle Charging Strategy

The increasing integration of renewable resources and electric vehicles (EVs) presents new requirements for the construction of a current distribution network. As an alternative of conventional distribution network, active distribution network (ADN) has gained more interest for its flexibility and interactivity. However, the unpredictable behavior of ADN participants from source-side, network-side, and demand-side brings more challenges on ADN dispatch. Thus, it is urged to design an ADN optimal scheduling approach that can comprehensively regulate the ADN participants' behavior. In this paper, an ADN performance assessment system is first established to provide a quantitative analysis on ADN's scheduling in terms of active controllability, active manageability, and active economy, respectively. Then, according to the ADN assessment system, a multi-stage optimal scheduling approach for ADN considering coordinated EV charging strategy is proposed. It is able to not only smooth the fluctuations caused by the integration of intermittent power sources and EVs but also reconfigure the network topology. Therefore, this approach can be applied to day-ahead dispatches to help operators effectively manage the ADN. Simulation results verify the correctness and effectiveness of the proposed approach.