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A valuation framework for customers impacted by extreme temperature-related outages

Author

Listed:
  • Yu, Min Gyung
  • Mukherjee, Monish
  • Poudel, Shiva
  • Bender, Sadie R.
  • Hanif, Sarmad
  • Hardy, Trevor D.
  • Reeve, Hayden M.

Abstract

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. These findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies.

Suggested Citation

  • Yu, Min Gyung & Mukherjee, Monish & Poudel, Shiva & Bender, Sadie R. & Hanif, Sarmad & Hardy, Trevor D. & Reeve, Hayden M., 2024. "A valuation framework for customers impacted by extreme temperature-related outages," Applied Energy, Elsevier, vol. 368(C).
    • Handle: RePEc:eee:appene:v:368:y:2024:i:c:s030626192400833x
    DOI: 10.1016/j.apenergy.2024.123450
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    References listed on IDEAS

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    1. Cheng-Chun Lee & Mikel Maron & Ali Mostafavi, 2022. "Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    2. Hanif, Sarmad & Mukherjee, Monish & Poudel, Shiva & Yu, Min Gyung & Jinsiwale, Rohit A. & Hardy, Trevor D. & Reeve, Hayden M., 2023. "Analyzing at-scale distribution grid response to extreme temperatures," Applied Energy, Elsevier, vol. 337(C).
    3. Viscusi, W Kip & Aldy, Joseph E, 2003. "The Value of a Statistical Life: A Critical Review of Market Estimates throughout the World," Journal of Risk and Uncertainty, Springer, vol. 27(1), pages 5-76, August.
    4. repec:reg:rpubli:282 is not listed on IDEAS
    5. Casey Zuzak & Matthew Mowrer & Emily Goodenough & Jordan Burns & Nicholas Ranalli & Jesse Rozelle, 2022. "The national risk index: establishing a nationwide baseline for natural hazard risk in the US," 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. 114(2), pages 2331-2355, November.
    6. Katharina Gruber & Tobias Gauster & Gregor Laaha & Peter Regner & Johannes Schmidt, 2022. "Profitability and investment risk of Texan power system winterization," Nature Energy, Nature, vol. 7(5), pages 409-416, May.
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    1. Zhang, Weiyi & Yang, Haibin & Cao, Xiangpeng & Bao, Xiaohua & Cui, Hongzhi, 2025. "A novel quantitative model for evaluating building energy resilience to maintain indoor thermal stability during peak power demand," Applied Energy, Elsevier, vol. 399(C).
    2. Shen, Jiawei & Pei, Ji & Wang, Wenjie & Yuan, Shouqi & Pavesi, Giorgio, 2025. "Broader high-efficiency zone of micro-pumped hydro storage enabled by a variable-speed reversible mixed-flow pump: Taking acceleration as an example," Renewable Energy, Elsevier, vol. 253(C).

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