Project

In practice, it is often difficult to incorporate empirical analyses of stakeholder behaviour into (techno-economic) energy system models. General energy system models often have a structure that does not allow for the mapping of micro-level stakeholder structures (e.g. they often have economic sectors as the smallest unit of analysis) due to their focus on macro-level phenomena or due to their model size. In principle, it is possible to model such stakeholder structures in techno-economic models that focus on a specific part of the energy system (e.g. the thermal conditioning of buildings). However, these models often already have a very high level of detail regarding the technologies under consideration. Therefore, the additional consideration of different stakeholder groups and subgroups and their interactions reaches practical limits in terms of justifiable model complexity and the resulting computational time. Therefore, the development of stand-alone agent-based models, in which it is possible to focus on socio-psychological aspects, represents an important research step.

The project aims to enable energy system models, despite their primarily techno-economic focus, to better incorporate the results of quantitative and qualitative empirical analyses (e.g. questionnaire studies, conjoint analyses, qualitative interviews, etc.) on stakeholder behaviour (e.g. citizens, companies, NGOs, etc.), and above all, to do so with less methodological effort. With regard to systems analysis, this should lead to particular progress in the area of model-related questions of technology acceptance and barrier analysis and enable a more realistic simulation and analysis of regulatory frameworks.

To achieve these goals, two agent-based models were (further) developed and coupled with energy system models: (1) A model focusing on the analysis of the stakeholder behaviour in innovation networks, i.e. actors involved in the research, development and production of new technologies. These include, in particular, companies and research institutes that generate new knowledge and exchange it through cooperation in order to develop new products (‘innovation model’). (2) The second model aims to model the acceptance of the policy by different stakeholders and how the interactions between them, as well as with intermediaries (such as installers and the media), can lead to increased or decreased acceptance. 

• Brugger, H.; Pröpper, A.; Bernath, C.; Droste-Franke, B.; Voge, M.; van Doren, D.; Dobbins, A.; Fahl, U.; Haller, K.; Wassermann, S.; Steinbach, J.; Senkpiel, C.; Thelen, C.; Nolte, H.; Kost, C.; Kockel, C.; Kulawik, J.; Wille, F.  (2023): Gemeinsamer Endbericht des Projektes „MANIFOLD: Modellentwicklung und Modellkopplung zu Akteursverhalten in Innovations- und Diffusionsnetzwerken“.
• Senkpiel, C.; Dobbins, A.; Kockel, C.; Steinbach, J.; Fahl, U.; Wille, F.; Globisch, J.; Wassermann, S.; Droste-Franke, B.; Hauser, W.; Hofer, C.; Nolting, L.; Bernath, C. (2020): Manifold. Integrating Methods and Empirical Findings from Social and Behavioural Sciences into Energy System Models—Motivation and Possible Approaches. In: Energies, 13 (18), p. 4951. https://doi.org/10.3390/en13184951.
• Globisch, J., Droste-Franke, B., Fohr, G., & Wassermann, S. (2019): Simulation von Innovationsdynamiken im Kontext der Energiewende. TATuP Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis, 29(3), 34–40. https://doi.org/10.14512/tatup.28.3.34.
• Brugger, H.; Pröpper, A.; Globisch, J.; Kleinschmitt, C.;  Droste-Franke, B.; Voge, M.; Dobbins, A.; Fahl, U.; Wassermann, S.; Hauser, W.; Steinbach, J.; Senkpiel, C.; Kockel, C.; Nolting, L.; Wille, F. (2023): Empirie und Modellschnittstellen. Anforderungen an Empirie als Input für Modelle sowie Schnittstellen zwischen Akteurs-, Diffusions-, Energiesystem- und Strommarktmodellen. Anhang A.1.3: Bericht zum Meilenstein 4. 
• Brugger, H.; Pröpper, A.; Kleinschmitt, C.;  Droste-Franke, B.; Voge, M.; Dobbins, A.; Haller, K.; Fahl, U.; Wassermann, S.; Hauser, W.; Steinbach, J.; Senkpiel, C.; Kockel, C.; Kulawik, J.; Wille, F. (2023): Empirie und Modellschnittstellen: Ergebnisse. Bericht zum Meilenstein 5. 
• Dobbins, A.; Fahl, U.; Haller, K.; Droste-Franke, B.; Voge, M.; Kockel, C.; Kulawik, J.; Brugger, H.; Pröpper, A.; Bernath, C.; Steinbach, J.; Senkpiel, C.; Wille, F. (2023): Manifold. Einbindung von empirischem Input in techno-ökonomische Modelle. Vor- und Nachteile unterschiedlicher Arten der Einbindung von empirischem Input in techno-ökonomische Modelle. Anhang A.1.5: Bericht zum Meilenstein 6.

October 2019 until September 2022

• Federal Ministry for Economic Affairs and Energy - BMWi

• RWTH Aachen University 
• Institut für Energiewirtschaft und Rationelle Energieanwendung IER  
• Fraunhofer-Institut für Solare Energiesysteme ISE 
• ZIRIUS - Zentrum für interdisziplinäre Risiko- und Innovationsforschung 
• Technische Universität Braunschweig IPMB
  
• IQIB – Institut für qualifizierende Innovationsforschung und -beratung gGmbH 
• IREES - Institut für Ressourceneffizienz und Energiestrategien