A two-stage adaptive-robust optimization model for active distribution network with high penetration wind power generation

High penetration of uncertain wind power generation brings challenges to power system operational security and economy. Here, an adjustable box uncertainty set is first presented to characterize the spatiotemporal correlation of multiple wind power generations. Afterward, a two-stage risk-adjusted robust energy dispatching model is established as a min-max-min optimization problem for active distribution networks operating with high penetration wind power generation. Then a three-layer Nest Column and Constraint Generation (NCCG) decomposition approach is designed to efficiently solve the proposed model. Finally, the proposed two-stage adaptive robust optimization model and NCCG approach are validated by a distribution network with uncertain wind power generations, and the simulation results indicate the distribution network operation economy could be compromised with robustness by adjusting the conservative regulation parameter. Here, an adjustable box uncertainty set is first presented to characterize the spatiotemporal correlation of multiple wind power generations. Afterward, a two-stage risk-adjusted robust energy dispatching model is established as a min-max-min optimization problem for active distribution networks operating with high penetration wind power generation. Then a three-layer Nest Column and Constraint Generation (NCCG) decomposition approach is designed to efficiently solve the proposed model.image