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Novel Multi-Criteria Decision Analysis Based on Performance Indicators for Urban Energy System Planning

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  • Benjamin Kwaku Nimako

    (Sustainable Development and Climate Change, University School for Advanced Studies IUSS, Piazza della Vittoria 15, 27100 Pavia, Italy
    Faculty of Engineering, Free University of Bozen-Bolzano, Piazza Domenicani 3, 39100 Bolzano, Italy)

  • Silvia Carpitella

    (Department of Manufacturing Systems Engineering and Management (MSEM), California State University, 18111 Nordhoff St., Los Angeles, CA 91330, USA)

  • Andrea Menapace

    (Eurac Research, Institute for Renewable Energy, 39100 Bolzano, Italy
    Faculty of Agricultural, Environmental and Food Sciences, Free University of Bozen-Bolzano, Piazza Università 5, 39100 Bolzano, Italy)

Abstract

Urban energy systems planning presents significant challenges, requiring the integration of multiple objectives such as economic feasibility, technical reliability, and environmental sustainability. Although previous studies have focused on optimizing renewable energy systems, many lack comprehensive decision frameworks that address the complex trade-offs between these objectives in urban settings. Addressing these challenges, this study introduces a novel Multi-Criteria Decision Analysis (MCDA) framework tailored for the evaluation and prioritization of energy scenarios in urban contexts, with a specific application to the city of Bozen-Bolzano. The proposed framework integrates various performance indicators to provide a comprehensive assessment tool, enabling urban planners to make informed decisions that balance different strategic priorities. At the core of this framework is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is employed to systematically rank energy scenarios based on their proximity to an ideal solution. This method allows for a clear, quantifiable comparison of diverse energy strategies, facilitating the identification of scenarios that best align with the city’s overall objectives. The flexibility of the MCDA framework, particularly through the adjustable criteria weights in TOPSIS, allows it to accommodate the shifting priorities of urban planners, whether they emphasize economic, environmental, or technical outcomes. The study’s findings underscore the importance of a holistic approach to energy planning, where trade-offs are inevitable but can be managed effectively through a structured decision-making process. Finally, the study addresses key gaps in the literature by providing a flexible and adaptable tool that can be replicated in different urban contexts to support the transition toward 100% renewable energy systems.

Suggested Citation

  • Benjamin Kwaku Nimako & Silvia Carpitella & Andrea Menapace, 2024. "Novel Multi-Criteria Decision Analysis Based on Performance Indicators for Urban Energy System Planning," Energies, MDPI, vol. 17(20), pages 1-18, October.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5207-:d:1502286
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    References listed on IDEAS

    as
    1. Kwon, Pil Seok & Østergaard, Poul Alberg, 2013. "Priority order in using biomass resources – Energy systems analyses of future scenarios for Denmark," Energy, Elsevier, vol. 63(C), pages 86-94.
    2. Wu, Desheng & Xie, Yu & Liu, Dingjie, 2023. "Rethinking the complex effects of the clean energy transition on air pollution abatement: Evidence from China's coal-to-gas policy," Energy, Elsevier, vol. 283(C).
    3. Lund, Henrik, 2007. "Renewable energy strategies for sustainable development," Energy, Elsevier, vol. 32(6), pages 912-919.
    4. Menapace, Andrea & Thellufsen, Jakob Zinck & Pernigotto, Giovanni & Roberti, Francesca & Gasparella, Andrea & Righetti, Maurizio & Baratieri, Marco & Lund, Henrik, 2020. "The design of 100 % renewable smart urb an energy systems: The case of Bozen-Bolzano," Energy, Elsevier, vol. 207(C).
    5. Shirley Thompson, 2023. "Strategic Analysis of the Renewable Electricity Transition: Power to the World without Carbon Emissions?," Energies, MDPI, vol. 16(17), pages 1-34, August.
    6. Prina, Matteo Giacomo & Lionetti, Matteo & Manzolini, Giampaolo & Sparber, Wolfram & Moser, David, 2019. "Transition pathways optimization methodology through EnergyPLAN software for long-term energy planning," Applied Energy, Elsevier, vol. 235(C), pages 356-368.
    7. Rozhkov, Anton, 2024. "Applying graph theory to find key leverage points in the transition toward urban renewable energy systems," Applied Energy, Elsevier, vol. 361(C).
    8. Li, Li & Wang, Jing & Zhong, Xiaoyi & Lin, Jian & Wu, Nianyuan & Zhang, Zhihui & Meng, Chao & Wang, Xiaonan & Shah, Nilay & Brandon, Nigel & Xie, Shan & Zhao, Yingru, 2022. "Combined multi-objective optimization and agent-based modeling for a 100% renewable island energy system considering power-to-gas technology and extreme weather conditions," Applied Energy, Elsevier, vol. 308(C).
    9. Yasmeen, Rizwana & Shah, Wasi Ul Hassan, 2024. "Energy uncertainty, geopolitical conflict, and militarization matters for Renewable and non-renewable energy development: Perspectives from G7 economies," Energy, Elsevier, vol. 306(C).
    10. Cayir Ervural, Beyzanur & Evren, Ramazan & Delen, Dursun, 2018. "A multi-objective decision-making approach for sustainable energy investment planning," Renewable Energy, Elsevier, vol. 126(C), pages 387-402.
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