Agent-Based Modelling of Urban District Energy System Decarbonisation—A Systematic Literature Review

Ardak Akhatova, Lukas Kranzl, Fabian Schipfer and Charitha Buddhika Heendeniya
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Ardak Akhatova: Energy Economics Group, Technische Universität Wien, Karlsplatz 13, A-1040 Vienna, Austria
Lukas Kranzl: Energy Economics Group, Technische Universität Wien, Karlsplatz 13, A-1040 Vienna, Austria
Fabian Schipfer: Energy Economics Group, Technische Universität Wien, Karlsplatz 13, A-1040 Vienna, Austria
Charitha Buddhika Heendeniya: Dipartimento Ambiente Costruzioni e Design, Scuola Universitaria Professionale Della Svizzera Italiana (SUPSI), Via Francesco Catenazzi 23, CH-6850 Mendrisio, Switzerland

Energies, 2022, vol. 15, issue 2, 1-27

Abstract: There is an increased interest in the district-scale energy transition within interdisciplinary research community. Agent-based modelling presents a suitable approach to address variety of questions related to policies, technologies, processes, and the different stakeholder roles that can foster such transition. However, it is a largely complex and versatile methodology which hinders its broader uptake by researchers as well as improved results. This state-of-the-art review focuses on the application of agent-based modelling for exploring policy interventions that facilitate the decarbonisation (i.e., energy transition) of districts and neighbourhoods while considering stakeholders’ social characteristics and interactions. We systematically select and analyse peer-reviewed literature and discuss the key modelling aspects, such as model purpose, agents and decision-making logic, spatial and temporal aspects, and empirical grounding. The analysis reveals that the most established agent-based models’ focus on innovation diffusion (e.g., adoption of solar panels) and dissemination of energy-saving behaviour among a group of buildings in urban areas. We see a considerable gap in exploring the decisions and interactions of agents other than residential households, such as commercial and even industrial energy consumers (and prosumers). Moreover, measures such as building retrofits and conversion to district energy systems involve many stakeholders and complex interactions between them that up to now have hardly been represented in the agent-based modelling environment. Hence, this work contributes to better understanding and further improving the research on transition towards decarbonised society.

Keywords: agent-based modelling; agent-based simulation; urban energy system; district energy system; systematic literature review; net-zero energy district; positive energy district (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: 2022
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Citations: View citations in EconPapers (6)

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