A robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets - Ye, Yuming; Wang, Jungang; Pan, Dingcai; Zhang, Jingsong; Li, Fan; Yin, Xueli (Frontiers in Energy Research, 2024)
In order to better describe the uncertainty of renewable energy output, this paper proposed a novel robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets. Firstly, an ellipsoidal uncertainty set was established using historical data of renewable energy output, and a data-driven convex hull polyhedral set was established by connecting high-dimensional ellipsoidal vertices; On this basis, an adaptive data driven polyhedral set model was established to address the problem of high conservatism in the scaling process of convex hull polyhedral sets. Furthermore, a novel adaptive data-driven robust scheduling model for new distribution systems was established, and a column and constraint (C&CG) generation algorithm was used to solve the robust scheduling model. Finally, the improved IEEE-33 bus system simulation verification shows that the robust scheduling model for new distribution systems based on adaptive data-driven polyhedral sets can reduce conservatism and improve the robustness of optimization results.