Modelling End-User Behavior and Behavioral Change in Smart Grids. An Application of the Model of Frame Selection

Sebastian Hoffmann, Fabian Adelt and Johannes Weyer
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Sebastian Hoffmann: Technology Studies Group, Faculty of Social Sciences, TU Dortmund University, 44227 Dortmund, Germany
Fabian Adelt: Technology Studies Group, Faculty of Social Sciences, TU Dortmund University, 44227 Dortmund, Germany
Johannes Weyer: Technology Studies Group, Faculty of Social Sciences, TU Dortmund University, 44227 Dortmund, Germany

Energies, 2020, vol. 13, issue 24, 1-26

Abstract: This paper presents an agent-based model (ABM) for residential end-users, which is part of a larger, interdisciplinary co-simulation framework that helps to investigate the performance of future power distribution grids (i.e., smart grid scenarios). Different modes of governance (strong, soft and self-organization) as well as end-users’ heterogeneous behavior represent key influential factors. Feedback was implemented as a measure to foster grid-beneficial behavior, which encompasses a range of monetary and non-monetary incentives (e.g., via social comparison). The model of frame selection (MFS) serves as theoretical background for modelling end-users’ decision-making. Additionally, we conducted an online survey to ground the end-user sub-model on empirical data. Despite these empirical and theoretical foundations, the model presented should be viewed as a conceptual framework, which requires further data collection. Using an example scenario, representing a lowly populated residential area (167 households) with a high share of photovoltaic systems (30%), different modes of governance were compared with regard to their suitability for improving system stability (measured in cumulated load). Both soft and strong control were able to decrease overall fluctuations as well as the mean cumulated load (by approx. 10%, based on weekly observation). However, we argue that soft control could be sufficient and more societally desirable.

Keywords: electricity feedback and consumption; governance; variable rationality; agent-based modelling; socio-technical aspects of energy systems; co-simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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