Association for Public Policy Analysis & Management

Energy system models can be used to produce actionable, policy relevant insight through rigorous exploration of the decision space that accounts for future uncertainty. This analysis employs an open source framework for energy system modeling – referred to as Tools for Energy Model Optimization and Analysis (Temoa) – to explore possible energy planning strategies in a hypothetical energy system. Two techniques are employed in this analysis. First, we conduct stochastic optimization, which encodes uncertain future outcomes into an event tree and simultaneously optimizes over all possible outcomes, each weighted by a subjective probability of occurrence. Second, we utilize modeling to generate alternatives (MGA), which systematically explores the near-optimal decision space by changing the structure of the model itself. Both techniques address the uncertainty inherent in future energy system development and provide a set of alternatives for decision makers to evaluate. We examine a diverse set of planning options that are revealed through the application of both techniques, which we assert could not be produced through conventional scenario analysis alone.