Multi-Time Scale Active and Reactive Power Coordinated Optimal Dispatch in Active Distribution Network Based on Scenario Method

Abstract

To improve the adaptability for renewable energy sources (RES), a multi-time scale optimal dispatching strategy based on the scenario method is proposed in the active distribution network (ADN). In the day-ahead stage, polynomial normal transformation and Latin hypercube sampling technology are employed to generate scenarios with temporal correlation. By optimizing the operation state of slow-response resources, the expected cost of ADN under all scenarios achieves a minimum. In the intraday stage, based on the updated predicted output of RES, the operation status of the fast-response resources is optimized using the same procedure. In the real-time stage, a rolling finite time-domain optimization strategy is adopted to minimize the deviation between the actual output and the intraday reference. Through the coordination of different time scales, the proposed method can reduce the action numbers of discrete reactive power compensation devices and restrain the fluctuation of bus voltage. A case study on a modified IEEE 33-bus system verified the economy and effectiveness of the proposed method.