Stochastic Economic Dispatching Strategy of the Active Distribution Network Based on Comprehensive Typical Scenario Set

The increasing penetration of renewable energy resources in the distribution network has posed great uncertainties and challenges for the system security operation. To model various uncertain factors like the wholesale market price and renewable energy generation in the active distribution network (ADN), a similarity measurement method considering the amplitude, volatility and variation trend is proposed. The Latin hypercube sampling method and Graph Pyramid clustering algorithm are adopted to obtain the comprehensive typical scenario set. Furthermore, this study proposes a scenario-based stochastic day-ahead optimal economic dispatch approach based on typical scenario set. The energy trading between the distribution system and the wholesale energy market, various distributed generators, network topology and power flow model are jointly formulated in the proposed operation model. The effectiveness and scalability of the proposed approach are verified using the IEEE 33-bus system. Numerical simulation results under different implementation scenarios indicate that the proposed approach offers a high computational efficiency and promotes the security and economy of the distribution system operation, which has a promising industrial application value.