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Resilient by design: Preventing wildfires and blackouts with microgrids

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  • Yang, Weijia
  • Sparrow, Sarah N.
  • Ashtine, Masaō
  • Wallom, David C.H.
  • Morstyn, Thomas

Abstract

This paper proposes a strategy for managing wildfire risks and preventing blackouts using microgrids. To demonstrate this approach, not seen in previous literature, we use the power network of Victoria, Australia, in December 2019 as a case study. The Fire Weather Index (FWI) is a crucial indicator of global fire behaviour both spatially and temporally, as proved with its robust analysis within many previous studies. The FWI is applied to a Wildfire-Energy System for the first time, contributing to a higher spatial and temporal resolution to position the wildfire risk in a grid. A novel method is proposed to automatically correlate the wildfire risk index and the power network model using geographical information of the transmission lines. The optimal power flow and grid performances are obtained from a grid model which incorporates wildfire risk distributions. It is shown that a system with installed microgrids can maintain operation under severe fire-related conditions without scheduled or unplanned outages. Finally, a cost-benefit analysis is conducted, which demonstrates that 68% of system costs can be recuperated by implementing networked microgrid solutions.

Suggested Citation

  • Yang, Weijia & Sparrow, Sarah N. & Ashtine, Masaō & Wallom, David C.H. & Morstyn, Thomas, 2022. "Resilient by design: Preventing wildfires and blackouts with microgrids," Applied Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:appene:v:313:y:2022:i:c:s0306261922002409
    DOI: 10.1016/j.apenergy.2022.118793
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    References listed on IDEAS

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    1. Blakers, Andrew & Lu, Bin & Stocks, Matthew, 2017. "100% renewable electricity in Australia," Energy, Elsevier, vol. 133(C), pages 471-482.
    2. Simshauser, P., 2021. "Rooftop Solar PV and the Peak Load Problem in the NEM’s Queensland Region," Cambridge Working Papers in Economics 2180, Faculty of Economics, University of Cambridge.
    3. David J. Frame & Suzanne M. Rosier & Ilan Noy & Luke J. Harrington & Trevor Carey-Smith & Sarah N. Sparrow & Dáithí A. Stone & Samuel M. Dean, 2020. "Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought," Climatic Change, Springer, vol. 162(2), pages 781-797, September.
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    1. Aili Amupolo & Sofia Nambundunga & Daniel S. P. Chowdhury & Gunnar Grün, 2022. "Techno-Economic Feasibility of Off-Grid Renewable Energy Electrification Schemes: A Case Study of an Informal Settlement in Namibia," Energies, MDPI, vol. 15(12), pages 1-32, June.
    2. Tomin, Nikita & Shakirov, Vladislav & Kurbatsky, Victor & Muzychuk, Roman & Popova, Ekaterina & Sidorov, Denis & Kozlov, Alexandr & Yang, Dechang, 2022. "A multi-criteria approach to designing and managing a renewable energy community," Renewable Energy, Elsevier, vol. 199(C), pages 1153-1175.
    3. Perera, A.T.D. & Zhao, Bingyu & Wang, Zhe & Soga, Kenichi & Hong, Tianzhen, 2023. "Optimal design of microgrids to improve wildfire resilience for vulnerable communities at the wildland-urban interface," Applied Energy, Elsevier, vol. 335(C).

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