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Electricity Load Lost in the Largest Windstorms—Is the Fragility-Based Model up to the Task?

Author

Listed:
  • Justinas Jasiūnas

    (School of Science, Aalto University, P.O. Box 15100, 00076 Espoo, Finland)

  • Ilona Láng-Ritter

    (Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland)

  • Tatu Heikkinen

    (School of Science, Aalto University, P.O. Box 15100, 00076 Espoo, Finland)

  • Peter D. Lund

    (School of Science, Aalto University, P.O. Box 15100, 00076 Espoo, Finland)

Abstract

Most existing models for estimating electric system impacts from windstorms tend to have detailed representation only for the electric or only for the meteorological system. As a result, there is little evidence on how models with detailed electric systems and realistic wind gust field representations would perform in different windstorm cases. This work explores the evidence for the ability of such a fragility-based model to generate realistic spatiotemporal lost load profiles for the most impactful windstorm cases in Finland. The literature review shows multiple driving factors for windstorm impacts that are difficult to assess analytically, and similarities between the most impactful windstorms. All the available interruption data for thirteen years were analyzed, with their grouping by individual storm and calm periods. The fixing of time distribution fits for these periods show most faults as being within the 20% uncertainty bounds of the severity-dependent distribution trendlines. The medium-voltage electricity grid impact model with national coverage was applied for the three most impactful and most recent windstorm cases, with the model calibrated for one case. The generated spatiotemporal lost load profiles in all cases recreate historic profiles within the similar error margins of approximately 20%.

Suggested Citation

  • Justinas Jasiūnas & Ilona Láng-Ritter & Tatu Heikkinen & Peter D. Lund, 2023. "Electricity Load Lost in the Largest Windstorms—Is the Fragility-Based Model up to the Task?," Energies, MDPI, vol. 16(15), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5678-:d:1205276
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    References listed on IDEAS

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    1. Roshanak Nateghi & Seth Guikema & Steven M. Quiring, 2014. "Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1069-1078, June.
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    4. D. Brent McRoberts & Steven M. Quiring & Seth D. Guikema, 2018. "Improving Hurricane Power Outage Prediction Models Through the Inclusion of Local Environmental Factors," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2722-2737, December.
    5. Jufri, Fauzan Hanif & Widiputra, Victor & Jung, Jaesung, 2019. "State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies," Applied Energy, Elsevier, vol. 239(C), pages 1049-1065.
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