Energy Systems Integration & Modeling Research Group

We develop models that can be divided into four main categories: • Operational models: Optimization models for the operation of electricity generation systems are developed and deployed. A Mixed Integer Linear Programming (MILP) framework is typically used for these Unit Commitment (UC) type problems. In terms of model development, the focus lies on improving the thermo-mechanical link, taking into account unpredictability in reserve sizing/allocation/activation, including new technologies (e.g., power-to-gas, thermal systems in buildings), integrating supply and demand side, and improving computational efficiency (e.g., tight problem formulation, parallel computing). • Expansion planning models: For energy planning and scenario analyses, long term models like TIMES are used. The technical operational detail of such planning models is increased, aiming to effectively bridge the gap between detailed operational models (unit commitment type) and long term energy technology planning models. • Equilibrium models: Equilibrium models describe the interactions of various (market) actors in the liberalized electric power sector (e.g., consumers, generators, policymakers). These models are used to analyze the impact of strategic behavior and market power on electricity markets, as well as the effect of market design or policy interventions on the electric power systems' performance. • Agent-based models: Agent-based models describe the electricity system as a complex adaptive system. This modeling approach captures the complex interactions among the physical infrastructure, the actors' behavior, and the institutions that govern those behaviors in a power system. Agent-based models are used to provide insights into, e.g., strategic behavior in electricity markets or the adoption of distributed energy resources, as well as to analyze the effect of policy interventions on the evolution of the electric power system.