Robust day-ahead dispatch for combined heat and power microgrid considering wind-solar power uncertainty

Due to the energy crisis and environment pollution, small-scale wind power and photovoltaics have been widely deployed in power system using microgrid (MG). Moreover, several researches have focused on incorporating various energy forms into MG. However, the uncertainties of wind power and photovoltaics may significantly impact the security and economy of the MG operation. To deal with this issue, this paper presents a two-stage robust model to achieve the optimal day-ahead economic dispatch strategy involving uncertain wind power and photovoltaics. The first stage decides the initial day-ahead dispatch strategy before the realization of uncertain wind power and photovoltaics. The additional adjustment action is made in the second stage as long as the uncertainties are observed. The column and constraint generation (C&CG) decomposition is employed to decompose the original model into the day-ahead dispatch master problem and the additional adjustment sub-problem. Based on the duality theory and Big-M approach, the sub-problem with complex max-min structure can be converted into a tractable mixed-integer linear programming (MILP) problem. Therefore, C&CG iteration algorithm can be further implemented to achieve the optimal day-ahead economic dispatch strategy for the MG. The experimental results of the comparisons to the deterministic optimization demonstrate the effectiveness of the presented optimization.