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Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models

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  • Roshanak Nateghi
  • Seth Guikema
  • Steven M. Quiring

Abstract

In this article, we discuss an outage‐forecasting model that we have developed. This model uses very few input variables to estimate hurricane‐induced outages prior to landfall with great predictive accuracy. We also show the results for a series of simpler models that use only publicly available data and can still estimate outages with reasonable accuracy. The intended users of these models are emergency response planners within power utilities and related government agencies. We developed our models based on the method of random forest, using data from a power distribution system serving two states in the Gulf Coast region of the United States. We also show that estimates of system reliability based on wind speed alone are not sufficient for adequately capturing the reliability of system components. We demonstrate that a multivariate approach can produce more accurate power outage predictions.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:riskan:v:34:y:2014:i:6:p:1069-1078
    DOI: 10.1111/risa.12131
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    References listed on IDEAS

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    1. Steven Quiring & Laiyin Zhu & Seth Guikema, 2011. "Importance of soil and elevation characteristics for modeling hurricane-induced power outages," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(1), pages 365-390, July.
    2. Liu, Haibin & Davidson, Rachel A. & Apanasovich, Tatiyana V., 2008. "Spatial generalized linear mixed models of electric power outages due to hurricanes and ice storms," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 897-912.
    3. Seung‐Ryong Han & Seth D. Guikema & Steven M. Quiring, 2009. "Improving the Predictive Accuracy of Hurricane Power Outage Forecasts Using Generalized Additive Models," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1443-1453, October.
    4. Han, Seung-Ryong & Guikema, Seth D. & Quiring, Steven M. & Lee, Kyung-Ho & Rosowsky, David & Davidson, Rachel A., 2009. "Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 199-210.
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    Cited by:

    1. Jasiūnas, Justinas & Heikkinen, Tatu & Lund, Peter D. & Láng-Ritter, Ilona, 2023. "Resilience of electric grid to extreme wind: Considering local details at national scale," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    2. Zhai, Chengwei & Chen, Thomas Ying-jeh & White, Anna Grace & Guikema, Seth David, 2021. "Power outage prediction for natural hazards using synthetic power distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    3. Xue, Jiayue & Mohammadi, Farshad & Li, Xin & Sahraei-Ardakani, Mostafa & Ou, Ge & Pu, Zhaoxia, 2020. "Impact of transmission tower-line interaction to the bulk power system during hurricane," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
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    5. 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.
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    7. Dennis Wagenaar & Tiaravanni Hermawan & Marc J. C. van den Homberg & Jeroen C. J. H. Aerts & Heidi Kreibich & Hans de Moel & Laurens M. Bouwer, 2021. "Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction," Risk Analysis, John Wiley & Sons, vol. 41(1), pages 37-55, January.
    8. Hughes, William & Zhang, Wei & Bagtzoglou, Amvrossios C. & Wanik, David & Pensado, Osvaldo & Yuan, Hao & Zhang, Jintao, 2021. "Damage modeling framework for resilience hardening strategy for overhead power distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    9. Wenjuan Sun & Paolo Bocchini & Brian D. Davison, 2020. "Applications of artificial intelligence for disaster management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2631-2689, September.
    10. Dimitris N. Trakas & Mathaios Panteli & Nikos D. Hatziargyriou & Pierluigi Mancarella, 2019. "Spatial Risk Analysis of Power Systems Resilience During Extreme Events," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 195-211, January.
    11. Gina L. Tonn & Seth D. Guikema & Celso M. Ferreira & Steven M. Quiring, 2016. "Hurricane Isaac: A Longitudinal Analysis of Storm Characteristics and Power Outage Risk," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1936-1947, October.
    12. Feifei Yang & Diego Cerrai & Emmanouil N. Anagnostou, 2021. "The Effect of Lead-Time Weather Forecast Uncertainty on Outage Prediction Modeling," Forecasting, MDPI, vol. 3(3), pages 1-16, July.
    13. Hughes, William & Zhang, Wei & Cerrai, Diego & Bagtzoglou, Amvrossios & Wanik, David & Anagnostou, Emmanouil, 2022. "A Hybrid Physics-Based and Data-Driven Model for Power Distribution System Infrastructure Hardening and Outage Simulation," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    14. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    15. Feifei Yang & David W. Wanik & Diego Cerrai & Md Abul Ehsan Bhuiyan & Emmanouil N. Anagnostou, 2020. "Quantifying Uncertainty in Machine Learning-Based Power Outage Prediction Model Training: A Tool for Sustainable Storm Restoration," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    16. Hughes, William & Watson, Peter L. & Cerrai, Diego & Zhang, Xinxuan & Bagtzoglou, Amvrossios & Zhang, Wei & Anagnostou, Emmanouil, 2024. "Assessing grid hardening strategies to improve power system performance during storms using a hybrid mechanistic-machine learning outage prediction model," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    17. Olukunle O. Owolabi & Deborah A. Sunter, 2022. "Bayesian Optimization and Hierarchical Forecasting of Non-Weather-Related Electric Power Outages," Energies, MDPI, vol. 15(6), pages 1-22, March.
    18. Berk A. Alpay & David Wanik & Peter Watson & Diego Cerrai & Guannan Liang & Emmanouil Anagnostou, 2020. "Dynamic Modeling of Power Outages Caused by Thunderstorms," Forecasting, MDPI, vol. 2(2), pages 1-12, May.
    19. 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.
    20. Tara C. Walsh & David W. Wanik & Emmanouil N. Anagnostou & Jonathan E. Mellor, 2020. "Estimated Time to Restoration of Hurricane Sandy in a Future Climate," Sustainability, MDPI, vol. 12(16), pages 1-27, August.

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