Incorporating institutions into optimization-based energy system models

The pledge for a carbon-free energy system in 2050 requires significant investments into renewable energy sources (RES). The relevant questions are: what technologies to select, where to build them, how much the capacities are, and at what cost. In order to answer these techno-economic questions, optimization models are commonly used to sketch a least-cost future energy system. However, the energy system is far more complex than a mathematical model. Although optimization models can provide the least-cost system design, they do not guarantee that we can realize this design because some key aspects are not captured by such models: the impact of public acceptance issues, conflicting interests among stakeholders, and the imperfection of markets. These non-technical aspects are generalized as institutions in this thesis. In a socio- technical system like the energy system, considering both the social aspects, the institutions, and the technical system, is pivotal. Therefore, the goal of this thesis is to improve optimization models by including institutions in energy system planning. Since institutions are not commonly mentioned in energy system planning models, this thesis starts with standardizing institutions, and we conducted a literature review. The goal is to provide a common ground for discussing institutions and find research trends and gaps in the state-of-the-art. We identified the following research gaps that need deliberate attention: spatial policies, collective decision-making, and bilateral trading with externalities. In this thesis, we developed three models to deal with these institutions. Since these institutions are indispensable in a socio-technical system, including them in optimization models results in socio-technically optimal future energy system designs beyond only the techno-economic optimums.Energie and Industri