The German Energiewende is a deliberate transformation of an established industrial economy towards a nearly CO2-free energy system accompanied by a phase out of nuclear energy. Its governance requires knowledge on how to steer the transition from the existing status quo to the target situation (transformation knowledge). The energy system is, however, a complex socio-technical system whose dynamics are influenced by behavioural and institutional aspects, which are badly represented by the dominant techno-economic scenario studies. In this paper, we therefore investigate and identify characteristics of model studies that make agent-based modelling supportive for the generation of transformation knowledge for the Energiewende. This is done by reflecting on the experiences gained from four different applications of agent-based models. In particular, we analyse whether the studies have improved our understanding of policies’ impacts on the energy system, whether the knowledge derived is useful for practitioners, how valid understanding derived by the studies is, and whether the insights can be used beyond the initial case-studies. We conclude that agent-based modelling has a high potential to generate transformation knowledge, but that the design of projects in which the models are developed and used is of major importance to reap this potential. Well-informed and goal-oriented stakeholder involvement and a strong collaboration between data collection and model development are crucial.@en

The transition process towards renewable energy systems is facing challenges in both fluctuating electricity generation of photovoltaic and wind power as well as socio-economic disruptions. With regard to sector integration, solutions need to be developed, especially for the mobility and the industry sector, because their ad hoc electrification and decarbonization seem to be unfeasible. Power-to-fuel (P2F) technologies may contribute to bridge the gap, as renewable energy can be transferred into hydrogen and hydrocarbon-based synthetic fuels. However, the renewable fuels production is far from economically competitive with conventional fuels. With a newly developed agent-based model, potential developments in the German energy markets were simulated for a horizon of 20 years from 2016 to 2035. The model was constructed through a participatory modeling process with relevant actors and stakeholders in the field. Model findings suggest that adjusted regulatory framework conditions (e.g., exemptions from electricity surtaxes, accurate prices for CO2-certificates, strong start-up subsidies, and drastic emission reduction quotas) are key factors for economically feasible P2F installations and will contribute to its large-scale integration into the German energy system. While plant capacities do not exceed 0.042 GW in a business-as-usual scenarios, the above-mentioned adjustments lead to plant capacities of at least 3.25 GW in 2035 with concurrent reduction in product prices.

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