Energy scheduling for microgrids with renewable energy sources considering an adjustable convex hull based uncertainty set

In this paper, a risk-based robust energy scheduling model for microgrids is proposed to address the uncertainty of renewable energy sources (RESs). The proposed model introduces a novel adjustable convex hull based uncertainty set (ACHUS), which is a subset of the maximum uncertainty set, to quantify the uncertainty of RESs. The operational risk of an ACHUS is evaluated by a historical data-based method. This method defines the operational risk as the expected penalty cost of all historical data when the operational safety of the microgrid is guaranteed in the ACHUS. Based on the evaluation of the operational risk, a day-ahead energy scheduling model with the ACHUS for microgrids is formulated as a mixed integer nonlinear programming. By introducing auxiliary variables and constraints, the mixed integer nonlinear programming is converted into a solvable mixed integer linear programming. The effectiveness of the proposed method is validated on the IEEE 6-bus and 118-bus systems. The simulation results show that the proposed method can effectively reduce the conservativeness of uncertainty quantification and the improve the economic efficiency of the microgrid.