A Two-Stage Robust Optimization Method for Microgrids Considering Wind Power and Photovoltaic Uncertainties

Microgrids play an important role in managing the increasingly developed renewable energy sources. As the primary renewable energy sources, the outputs of wind power and photovoltaics show a lot of uncertainties influenced by meteorological factors. These uncertainties can have adverse effects on the economic efficiency of microgrid operations. We have established a two-stage robust optimization model tailored for microgrids considering wind power and photovoltaics to address this issue. In this model, a box uncertainty set of wind power and PVs that can be quantitatively adjusted is proposed. The two-stage model is a Mixed-Integer Programming (MIP) model, which belongs to an NP-hard problem. Therefore, we choose the Columns and Constraints Generation Algorithm (C&CG) to solve the model. Finally, the practical validity of our model is demonstrated through the results obtained from its application to the modified IEEE-39 bus system.