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Article

Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies

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Wuppertal Institute for Climate, Environment and Energy, Döppersberg 19, 42103 Wuppertal, Germany
2
Department of Technological Design and Development, University of Bremen, Badgasteiner Str. 1, 28359 Bremen, Germany
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Centre for Sustainable Energy Technology Research, Stuttgart University of Applied Sciences, Schellingstraße 24, 70174 Stuttgart, Germany
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Department of Innovation Economics (520i), University of Hohenheim, Schloss Hohenheim 1, 70599 Stuttgart, Germany
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Energy and Industry Group, Faculty of Technology, Policy and Management, Delft University of Technology, 2628 BX Delft, The Netherlands
*
Author to whom correspondence should be addressed.
Energies 2020, 13(22), 6133; https://doi.org/10.3390/en13226133
Received: 1 October 2020 / Revised: 13 November 2020 / Accepted: 17 November 2020 / Published: 23 November 2020
(This article belongs to the Special Issue Agent-Based Modeling of Socioeconomic Challenges of Energy Transition)
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. View Full-Text
Keywords: energiewende; energy; transition; transformation knowledge; agent-based model; insulation; retail market; feedback products; power-to-fuels energiewende; energy; transition; transformation knowledge; agent-based model; insulation; retail market; feedback products; power-to-fuels
MDPI and ACS Style

Holtz, G.; Schnülle, C.; Yadack, M.; Friege, J.; Jensen, T.; Thier, P.; Viebahn, P.; Chappin, É.J.L. Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies. Energies 2020, 13, 6133. https://doi.org/10.3390/en13226133

AMA Style

Holtz G, Schnülle C, Yadack M, Friege J, Jensen T, Thier P, Viebahn P, Chappin ÉJL. Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies. Energies. 2020; 13(22):6133. https://doi.org/10.3390/en13226133

Chicago/Turabian Style

Holtz, Georg, Christian Schnülle, Malcolm Yadack, Jonas Friege, Thorben Jensen, Pablo Thier, Peter Viebahn, and Émile J.L. Chappin 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies" Energies 13, no. 22: 6133. https://doi.org/10.3390/en13226133

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