Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization
Ye He, Hongyun Fu, Yang Wu, Hongbin Wu, Ming Ding
Abstract
• A DN fault modeling that considers the load impacts and secondary disasters is proposed. • Two types of resilience indices are constructed to evaluate the resilience level of the DN. • A two-stage robust optimization strategy for ESS under extreme weather conditions is built. • The proposed model achieves a balance of resilience and economy of the DN. • Results were implemented to verify the effectiveness of the proposed strategy. Extreme natural disasters can easily cause large-scale power outages in distribution networks (DN), and energy storage system (ESS) contributes to an essential part of integrated solutions to this problem owing to its flexible regulation and rapid response characteristics. A two-stage robust optimization model for ESS that considers the resilience enhancement of a DN under extreme weather conditions is proposed. First, the impacts of secondary hazards on the component failure rates were quantified, and a time-varying matrix of distribution line failures was constructed. Second, an overall recovery index of the DN and an important load recovery index were proposed. Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). Furthermore, numerous simulations were performed on the IEEE 33-node system, and it showed that the proposed method can not only ensure the optimal comprehensive economics of the ESS and fully tap the support potential of the ESS, but also maximize the resilience of the DN. Compared to the DN without energy storage system, the proposed method improves the overall resilience and important load recovery of the DN by about 15.9% and 4.3%, respectively.