Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model

This paper presents a new uncertainty handling framework for optimal generation expansion planning (GEP) amalgamating the notions of single-stage and two-stage robust optimization (RO). The proposed multiyear robust GEP methodology, as a tractable mixed integer linear programming optimization problem, copes with the inherent planning uncertainties associated with forecasted electricity load demand, as well as estimated investment and operation costs through distribution-free bounded intervals producing polyhedral uncertainty sets. The optimal generation expansion plan obtained from the proposed RO approach is immunized against worst-case planning uncertainties considering the adopted degree of conservatism for each uncertainty set. Therefore, the proposed methodology is capable of controlling the robustness of the optimal investment schedule regarding the enforced planning uncertainties. Simulation results demonstrate the efficacy and efficiency of the proposed RO framework throughout GEP studies.