Coping with Uncertainties in the Electricity Sector – Methods for Decisions of Different Scope

Decision-making in the energy sector and notably the power industry has to cope with multiple uncertain factors such as renewable forecasts, technology developments or demand growth. At the same time, multiple methods are available to support decision-making under uncertainty. The focus of the present review is to identify the merits of different optimization modelling approaches regarding various types of decision problems under uncertainty with a focus on the electricity system. Stochastic optimization and robust optimization are scrutinized along with other, less known methods like information gap decision theory (IGDT) or modeling-to-generate-alternatives (MGA). Also, simple deterministic equivalents, scenario and sensitivity analyses are considered when it comes to solving operational decision problems, investment decisions and policy choices regarding regulatory settings. The latter deserve particular scrutiny in a context of decarbonization and energy system transformation which embraces several decades and multiple decision makers in a multi-level governance context.