Actor DynaMics In energy Transitions at the municipal level

Due to the complexity of continuously evolving energy systems, quantitative model-based analysis at the municipal level is decisive for determining optimal energy transition pathways. Despite the suggestions of numerous studies, the practical adoption of the energy technologies required to deliver substantial reductions in emissions too often shows little success. The problem is not simply one of technological diffusion but of systemic enforcement. Existing transition concepts hardly show relevant process dynamics since the applied energy system models leave market actors outside the scope. Quantitative analyses are mostly undertaken with a centralized planning approach under the selected objective of techno-economic feasibility, and sometimes qualitatively enriched with socio-economic aspects. In order to tackle issues of practical implementation, future models need to be able to capture and demonstrate the socio-technical energy transition pathways in a spatial-temporal context.

The research project ADMIT aims to design and develop novel energy system methods and models that not only quantify optimal technical transition pathways within a spatial context but also demonstrate the temporal course of stakeholders’ responsibilities. Since techno-economic modelling is quite mature, the focus is on socio-economic modelling. Concerning this matter, both process models as well as modelling approaches are to be challenged since neither current conceptual frameworks nor mathematical programming adequately address stakeholder dynamics with respect to low carbon technology adoption. In doing so, a two-step research design is applied. Building upon empirical insights and conceptual models, a stakeholder governance framework is initially constructed. This framework is refined through multiple case studies around a focal technology diffusion process at the municipal level. Subsequently, proven quantitative models are extended by the formalized theory. The realized model accuracy is validated with the historical data of the case studies. Consequently, this research output contributes to the current discussions within heterogeneity of decision-making and socio-technical energy transitions.