A novel conceptual model facilitating the derivation of agent-based models for analyzing socio-technical optimality gaps in the energy domain. (15th October 2017)

• Record Type: Journal Article
• Authors: Hinker, Jonas; Hemkendreis, Christian; Drewing, Emily; März, Steven; Hidalgo Rodríguez, Diego I.; Myrzik, Johanna M.A.
• Is Part Of: Energy. Volume 137(2017)
• Page Start: 1219
• Page End: 1230
• Publication Date: 2017-10-15
• Subjects: Socio-technical systems -- Energy systems -- Actor-centered modeling -- Multi-actor systems -- Conceptual modeling -- Agent-based modeling; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2017.06.038
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Optimization and simulation models are fit to work on a multitude of technical, economic, and techno-economic questions. However, they are by now not able to satisfactorily include societal aspects like acceptance, spatial implications and legal frameworks. In order to advance scope and explanatory power of simulation models, collaboration in interdisciplinary research teams is needed. Yet the exchange in such teams and its coordination can prove challenging. Furthermore, disciplinary approaches and methods for simulation and optimization might not be familiar to all participants. To this end, a new conceptual model is introduced. The conceptual model employs few basic elements and concepts for describing and explaining arbitrary societal and technical relationships. Most notably, the conceptual model is general in its design, so contributions to the problem formulation and design components can be made by all team members regardless of their discipline. The procedure is based on common agent-based concepts without using their terminology. Consequently, an exchange among all team members becomes possible without them necessarily being proficient in agent-based modeling. A reduced presentation of workshop results exemplifies the use of novel elements for deriving an emergent agent-based simulation. Highlights: Deriving agent-based models (ABM) is rendered possible without proficiency in ABM. Socio-technical optimality gaps address essential challenges of the energy transition. Suggested terminology is general and tailored to the needs of interdisciplinary teams. Future studies can avoid counterintuitive outcomes using this concept.