Regional-scale electric power system planning under uncertainty—A multistage interval-stochastic integer linear programming approach

In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed for supporting electric power system (EPS) planning under uncertainty that is based on a multistage interval-stochastic integer linear programming method. The developed MIS-REM can deal with uncertainties expressed as both probability distributions and interval values existing in energy system planning problems. Moreover, it can reflect dynamic decisions for electricity generation schemes and capacity expansions through transactions at discrete points of a multiple representative scenario set over a multistage context. It can also analyze various energy-policy scenarios that are associated with economic penalties when the regulated targets are violated. A case study is provided for demonstrating the applicability of the developed model, where renewable and non-renewable energy resources, economic concerns, and environmental requirements are integrated into a systematic optimization process. The results obtained are helpful for supporting (a) adjustment or justification of allocation patterns of regional energy resources and services, (b) formulation of local policies regarding energy consumption, economic development, and energy structure, and (c) analysis of interactions among economic cost, environmental requirement, and energy-supply security.