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Designing backcasting scenarios for resilient energy futures

Author

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  • Kishita, Yusuke
  • McLellan, Benjamin C.
  • Giurco, Damien
  • Aoki, Kazumasu
  • Yoshizawa, Go
  • Handoh, Itsuki C.

Abstract

The concept of resilience is a crucial part in crafting visions of desirable futures designed to withstand the widest variety of external shocks to the system. Backcasting scenarios are widely used to envision desirable futures with a discontinuous change from the present in mind. However, less effort has been devoted to developing theoretical frameworks and methods for building backcasting scenarios with a particular focus on resilience, although resilience has been explored in related sustainability fields. This paper proposes a method that helps design backcasting scenarios for resilient futures. A characteristic of the method is to delineate “collapse” futures, based upon which resilient futures are described to avoid the various collapsed states. In the process of designing backcasting scenarios, fault tree analysis (FTA) is used to support the generation of various risk factors and countermeasures to improve resilience. In order to test the effectiveness of the proposed method, we provide a case study to describe resilient energy systems for a Japanese community to 2030. Four expert workshops involving researchers from different disciplines were organized to generate diversified ideas on resilient energy systems. The results show that three scenarios of collapsed energy systems were described, in which policy options to be taken toward achieving resilient energy systems were derived.

Suggested Citation

  • Kishita, Yusuke & McLellan, Benjamin C. & Giurco, Damien & Aoki, Kazumasu & Yoshizawa, Go & Handoh, Itsuki C., 2017. "Designing backcasting scenarios for resilient energy futures," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 114-125.
    • Handle: RePEc:eee:tefoso:v:124:y:2017:i:c:p:114-125
    DOI: 10.1016/j.techfore.2017.02.001
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    Cited by:

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    2. Pereverza, Kateryna & Pasichnyi, Oleksii & Kordas, Olga, 2019. "Modular participatory backcasting: A unifying framework for strategic planning in the heating sector," Energy Policy, Elsevier, vol. 124(C), pages 123-134.
    3. Matti Grosse & Hendrik Send & Thomas Schildhauer, 2019. "Lessons Learned from Establishing the Energy-Informatics Business Model: Case of a German Energy Company," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    4. Khrisydel Rhea M. Supapo & Lorafe Lozano & Ian Dominic F. Tabañag & Edward M. Querikiol, 2022. "A Backcasting Analysis toward a 100% Renewable Energy Transition by 2040 for Off-Grid Islands," Energies, MDPI, vol. 15(13), pages 1-19, June.
    5. Patricia Abduragimova & Brian D. Fath & Christian Gulas & Harald Katzmair, 2023. "Participatory approach for assessing institutional resilience: a case study of crises in Austria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9201-9225, September.
    6. Kishita, Yusuke & Höjer, Mattias & Quist, Jaco, 2024. "Consolidating backcasting: A design framework towards a users’ guide," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    7. Parra, Juan Felipe & Olaya, Yris & Arango-Aramburo, Santiago, 2024. "Perspective on the human dimension in energy modelling: Structural analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    8. Sarkki, Simo & Pihlajamäki, Mia, 2019. "Baltic herring for food: Shades of grey in how backcasting recommendations work across exploratory scenarios," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 200-209.
    9. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F. & Pousinho, H.M.I., 2019. "Decision making for sustainable aggregation of clean energy in day-ahead market: Uncertainty and risk," Renewable Energy, Elsevier, vol. 133(C), pages 692-702.

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