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Projecting future costs to U.S. electric utility customers from power interruptions

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  • Larsen, Peter H.
  • Boehlert, Brent
  • Eto, Joseph
  • Hamachi-LaCommare, Kristina
  • Martinich, Jeremy
  • Rennels, Lisa

Abstract

This analysis integrates regional models of power system reliability, output from atmosphere-ocean general circulation models, and results from the Interruption Cost Estimate (ICE) Calculator to project long-run costs to electric utility customers from power interruptions under different future severe weather and electricity system scenarios. We discuss the challenges when attempting to model long-run costs to utility customers including the use of imperfect metrics to measure severe weather. Despite these challenges, initial findings show that discounted cumulative customer costs, through the middle of the century, could range from $1.5-$3.4 trillion ($2015) without aggressive undergrounding of the power system and increased utility operations and maintenance (O&M) spending and $1.5-$2.5 trillion with aggressive undergrounding and increased spending. By the end of the century, cumulative customer costs could range from $1.9-$5.6 trillion (without aggressive undergrounding and increased spending) and $2.0-$3.6 trillion (with aggressive undergrounding and increased spending). We find that, in some scenarios, aggressive undergrounding of distribution lines and increased O&M spending is not always cost-effective. We conclude by identifying important topics for follow-on research, which have the potential to improve the cost estimates of this model.

Suggested Citation

  • Larsen, Peter H. & Boehlert, Brent & Eto, Joseph & Hamachi-LaCommare, Kristina & Martinich, Jeremy & Rennels, Lisa, 2018. "Projecting future costs to U.S. electric utility customers from power interruptions," Energy, Elsevier, vol. 147(C), pages 1256-1277.
  • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:1256-1277
    DOI: 10.1016/j.energy.2017.12.081
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    1. Erdogdu, Erkan, 2011. "The impact of power market reforms on electricity price-cost margins and cross-subsidy levels: A cross country panel data analysis," Energy Policy, Elsevier, vol. 39(3), pages 1080-1092, March.
    2. Larsen, Peter H., 2016. "A method to estimate the costs and benefits of undergrounding electricity transmission and distribution lines," Energy Economics, Elsevier, vol. 60(C), pages 47-61.
    3. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    4. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    5. Evan Mills & Richard B Jones, 2016. "An Insurance Perspective on U.S. Electric Grid Disruption Costs," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 41(4), pages 555-586, October.
    6. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    7. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    8. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    9. LaCommare, Kristina Hamachi & Eto, Joseph H., 2006. "Cost of power interruptions to electricity consumers in the United States (US)," Energy, Elsevier, vol. 31(12), pages 1845-1855.
    10. Hines, Paul & Apt, Jay & Talukdar, Sarosh, 2009. "Large blackouts in North America: Historical trends and policy implications," Energy Policy, Elsevier, vol. 37(12), pages 5249-5259, December.
    11. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    12. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    13. Larsen, Peter H. & LaCommare, Kristina H. & Eto, Joseph H. & Sweeney, James L., 2016. "Recent trends in power system reliability and implications for evaluating future investments in resiliency," Energy, Elsevier, vol. 117(P1), pages 29-46.
    14. David Ward, 2013. "The effect of weather on grid systems and the reliability of electricity supply," Climatic Change, Springer, vol. 121(1), pages 103-113, November.
    15. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
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    Cited by:

    1. 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).
    2. Larsen, Peter H. & Lawson, Megan & LaCommare, Kristina H. & Eto, Joseph H., 2020. "Severe weather, utility spending, and the long-term reliability of the U.S. power system," Energy, Elsevier, vol. 198(C).
    3. Ye, Bin & Jiang, Jingjing & Liu, Junguo & Zheng, Yi & Zhou, Nan, 2021. "Research on quantitative assessment of climate change risk at an urban scale: Review of recent progress and outlook of future direction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    4. Chen, Hao & Yan, Haobo & Gong, Kai & Geng, Haopeng & Yuan, Xiao-Chen, 2022. "Assessing the business interruption costs from power outages in China," Energy Economics, Elsevier, vol. 105(C).
    5. Thomas, Douglas & Fung, Juan, 2022. "Measuring downstream supply chain losses due to power disturbances," Energy Economics, Elsevier, vol. 114(C).
    6. Chen, Haoling & Zhao, Tongtiegang, 2020. "Modeling power loss during blackouts in China using non-stationary generalized extreme value distribution," Energy, Elsevier, vol. 195(C).
    7. Abadie, Luis Ma & Chamorro, José M., 2019. "Physical adequacy of a power generation system: The case of Spain in the long term," Energy, Elsevier, vol. 166(C), pages 637-652.
    8. Richard Wallsgrove & Jisuk Woo & Jae-Hyup Lee & Lorraine Akiba, 2021. "The Emerging Potential of Microgrids in the Transition to 100% Renewable Energy Systems," Energies, MDPI, vol. 14(6), pages 1-28, March.

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    More about this item

    Keywords

    Electric system reliability; Grid resilience; Power outages; Outage cost; Severe weather; Undergrounding; Q4 energy; Q5 environmental economics; R00 general; O2 development planning and policy;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy

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