Robust Microgrid Capacity Investment With Endogenous and Exogenous Uncertainties
Hossein Haghighat, Wei Wang, Bo Zeng
Abstract
Microgrid deployment is an effective measure to enhance grid resilience and flexibility. This research presents a two-stage robust model for microgrid planning, considering mixed decision-dependent and decision-independent uncertainties. We design a modern time-of-use (ToU) pricing scheme to optimize the identification of peak/off-peak time periods, as well as the pricing for individual load buses. The operational constraints of the recourse problem are characterized using a second-order conic AC power flow model. To exactly solve this intricate microgrid design problem, we devise a parametric CCG procedure that can handle robust optimization programs with hybrid endogenous and exogenous uncertainties. The proposed methodology is illustrated using three test systems, and the experimental results are discussed with a set of novel insights.