A Novel Uncertainty Budget Optimization Method for Hybrid AC/DC Microgrids with High-penetration Renewable Generation

Uncertainties from the increasing penetration of renewable energy generation (REG) have introduced numerous challenges to energy management of microgrids. In this paper, a novel risk-based uncertainty set optimization method is proposed for the energy management of typical hybrid AC/DC microgrids where REG outputs are considered as the major uncertainties. The underlying risks of renewable power curtailment and load shedding are formulated in detail based on the probabilistic distribution of RGE forecasted value, and are further considered in the objective functions. Finally, the proposed model is reformulated to a MILP problem and effectively solved by high-performance solver. A case study on a real AC/DC hybrid microgrids system in East China demonstrate the effectiveness, good applicability and robustness of the proposed model, particularly in comparison to the typical robust optimization method.