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

Author

Listed:
  • 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
    Current address: Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA.)

  • Charitha Buddhika Heendeniya

    (Dipartimento Ambiente Costruzioni e Design, Scuola Universitaria Professionale Della Svizzera Italiana (SUPSI), Via Francesco Catenazzi 23, CH-6850 Mendrisio, Switzerland)

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.

Suggested Citation

  • Ardak Akhatova & Lukas Kranzl & Fabian Schipfer & Charitha Buddhika Heendeniya, 2022. "Agent-Based Modelling of Urban District Energy System Decarbonisation—A Systematic Literature Review," Energies, MDPI, vol. 15(2), pages 1-27, January.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:554-:d:723847
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    Citations

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    Cited by:

    1. Tobias Mueller & Steven Gronau, 2023. "Fostering Macroeconomic Research on Hydrogen-Powered Aviation: A Systematic Literature Review on General Equilibrium Models," Energies, MDPI, vol. 16(3), pages 1-33, February.
    2. Amir Ali Safaei Pirooz & Mohammad J. Sanjari & Young-Jin Kim & Stuart Moore & Richard Turner & Wayne W. Weaver & Dipti Srinivasan & Josep M. Guerrero & Mohammad Shahidehpour, 2023. "Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation," Energies, MDPI, vol. 16(8), pages 1-16, April.
    3. Kazeem Alasinrin Babatunde & Moamin A. Mahmoud & Nazrita Ibrahim & Fathin Faizah Said, 2023. "Malaysia’s Electricity Decarbonisation Pathways: Exploring the Role of Renewable Energy Policies Using Agent-Based Modelling," Energies, MDPI, vol. 16(4), pages 1-15, February.

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