IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v30y2010i12p1744-1752.html
   My bibliography  Save this article

Prestorm Estimation of Hurricane Damage to Electric Power Distribution Systems

Author

Listed:
  • Seth D. Guikema
  • Steven M. Quiring
  • Seung‐Ryong Han

Abstract

Hurricanes frequently cause damage to electric power systems in the United States, leading to widespread and prolonged loss of electric service. Restoring service quickly requires the use of repair crews and materials that must be requested, at considerable cost, prior to the storm. U.S. utilities have struggled to strike a good balance between over‐ and underpreparation largely because of a lack of methods for rigorously estimating the impacts of an approaching hurricane on their systems. Previous work developed methods for estimating the risk of power outages and customer loss of power, with an outage defined as nontransitory activation of a protective device. In this article, we move beyond these previous approaches to directly estimate damage to the electric power system. Our approach is based on damage data from past storms together with regression and data mining techniques to estimate the number of utility poles that will need to be replaced. Because restoration times and resource needs are more closely tied to the number of poles and transformers that need to be replaced than to the number of outages, this pole‐based assessment provides a much stronger basis for prestorm planning by utilities. Our results show that damage to poles during hurricanes can be assessed accurately, provided that adequate past damage data are available. However, the availability of data can, and currently often is, the limiting factor in developing these types of models in practice. Opportunities for further enhancing the damage data recorded during hurricanes are also discussed.

Suggested Citation

  • Seth D. Guikema & Steven M. Quiring & Seung‐Ryong Han, 2010. "Prestorm Estimation of Hurricane Damage to Electric Power Distribution Systems," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1744-1752, December.
  • Handle: RePEc:wly:riskan:v:30:y:2010:i:12:p:1744-1752
    DOI: 10.1111/j.1539-6924.2010.01510.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2010.01510.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.2010.01510.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Fant, Charles & Boehlert, Brent & Strzepek, Kenneth & Larsen, Peter & White, Alisa & Gulati, Sahil & Li, Yue & Martinich, Jeremy, 2020. "Climate change impacts and costs to U.S. electricity transmission and distribution infrastructure," Energy, Elsevier, vol. 195(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).
    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. 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).
    6. 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.
    7. 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).
    8. Jichao He & David W. Wanik & Brian M. Hartman & Emmanouil N. Anagnostou & Marina Astitha & Maria E. B. Frediani, 2017. "Nonparametric Tree‐Based Predictive Modeling of Storm Outages on an Electric Distribution Network," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 441-458, March.
    9. Gonzalo L. Pita, 2015. "Review of CAPRA Vulnerability Module (Hurricane Suite)," World Bank Publications - Reports 22981, The World Bank Group.
    10. 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.
    11. Diana Mitsova & Ann-Margaret Esnard & Alka Sapat & Betty S. Lai, 2018. "Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma," 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. 94(2), pages 689-709, November.
    12. Zhang, Jintao & Bagtzoglou, Yiannis & Zhu, Jin & Li, Baikun & Zhang, Wei, 2023. "Fragility-based system performance assessment of critical power infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    13. Yi‐Ping Fang & Giovanni Sansavini & Enrico Zio, 2019. "An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1949-1969, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Seung‐Ryong Han & David Rosowsky & Seth Guikema, 2014. "Integrating Models and Data to Estimate the Structural Reliability of Utility Poles During Hurricanes," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1079-1094, June.
    3. Hui Hou & Shiwen Yu & Hongbin Wang & Yong Huang & Hao Wu & Yan Xu & Xianqiang Li & Hao Geng, 2019. "Risk Assessment and Its Visualization of Power Tower under Typhoon Disaster Based on Machine Learning Algorithms," Energies, MDPI, vol. 12(2), pages 1-23, January.
    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. 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.
    6. Oh, Seongmun & Jufri, Fauzan Hanif & Choi, Min-Hee & Jung, Jaesung, 2022. "A study of tropical cyclone impact on the power distribution grid in South Korea for estimating damage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    7. Hou, Hui & Liu, Chao & Wei, Ruizeng & He, Huan & Wang, Lei & Li, Weibo, 2023. "Outage duration prediction under typhoon disaster with stacking ensemble learning," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    8. 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).
    9. 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.
    10. 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).
    11. 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.
    12. Roshanak Nateghi & Seth D. Guikema & Yue (Grace) Wu & C. Bayan Bruss, 2016. "Critical Assessment of the Foundations of Power Transmission and Distribution Reliability Metrics and Standards," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 4-15, January.
    13. Roshanak Nateghi & Seth D. Guikema & Steven M. Quiring, 2011. "Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1897-1906, December.
    14. Royce A. Francis & Srinivas Reddy Geedipally & Seth D. Guikema & Soma Sekhar Dhavala & Dominique Lord & Sarah LaRocca, 2012. "Characterizing the Performance of the Conway‐Maxwell Poisson Generalized Linear Model," Risk Analysis, John Wiley & Sons, vol. 32(1), pages 167-183, January.
    15. Mukherjee, Sayanti & Nateghi, Roshanak & Hastak, Makarand, 2018. "A multi-hazard approach to assess severe weather-induced major power outage risks in the U.S," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 283-305.
    16. Otto, Räisänen & Susanne, Suvanto & Jouni, Haapaniemi & Jukka, Lassila, 2023. "Crown snow load outage risk model for overhead lines," Applied Energy, Elsevier, vol. 343(C).
    17. Mahyar Ghorbanzadeh & Mohammadreza Koloushani & Mehmet Baran Ulak & Eren Erman Ozguven & Reza Arghandeh Jouneghani, 2020. "Statistical and Spatial Analysis of Hurricane-induced Roadway Closures and Power Outages," Energies, MDPI, vol. 13(5), pages 1-18, March.
    18. Jichao He & David W. Wanik & Brian M. Hartman & Emmanouil N. Anagnostou & Marina Astitha & Maria E. B. Frediani, 2017. "Nonparametric Tree‐Based Predictive Modeling of Storm Outages on an Electric Distribution Network," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 441-458, March.
    19. Maliszewski, Paul J. & Larson, Elisabeth K. & Perrings, Charles, 2012. "Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 161-171.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:30:y:2010:i:12:p:1744-1752. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.