Risk Tolerance, Aversion, and Economics of Energy Utilities in Community Resilience to Wildfires
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 2
Abstract
Electric and gas investor-owned utilities operate in a regulated environment and are scrutinized by media and stakeholders for key strategic and operational decisions. Some decisions entail significant risk, requiring special attention to risk tolerances and attitudes including risk aversion. Utilities typically institute enterprise risk management programs to efficiently and effectively manage safety, reliability, and financial risks for their customers, employees, and communities in a changing climate with intensifying risks, such as wildfire. Consequences from such events could include human life and property losses, health effects, environmental damage, service loss, and other indirect financial and economic impacts. A spectrum of risk quantification and management methods are available for assessing these hazards. Varying risk tolerances and attitudes of stakeholders creates situations that are central to decision-making where the safety, service delivery reliability, rate affordability, and the financial wellbeing of entities come together and interact in a complex manner. This paper sets context, defines key terms, and develops an innovative approach for methodically reflecting risk tolerance and attitude with a focus on risk aversion in informing risk management decisions by offering flexibility to account for preferences by stakeholders in a structured manner. The concept of risk-aversion amplification factors is proposed to reflect attitudes and preferences of decision makers in typical economic models used in benefit-cost analysis. Such amplification factors can be calibrated by applicable markets, such as insurance and catastrophe bond markets and used to estimate certainty-equivalent valuations of risks, costs, and benefits. The proposed methods are illustrated in the context of wildfire risk management for communities and utilities using two examples from these domains for enhancing resilience.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors acknowledge the input of T. Brown and A. Tzamaras; and reviews by A. Maranghides, Dr. S. W. Gilbert, and T. Ibn Faiz; the guidance of R. Ito and A. Mani; and input of S. Elsibaie, C.C. Gore, and Ryan Flynn-deOnis. The financial support of Pacific Gas and Electric (PG&E), KPMG LLP, the National Institute of Standards and Technology (NIST), and BMA Engineering, Inc. is acknowledged.
Disclaimer
Statements in the paper are those of the authors and do not represent views of sponsors nor a consensus that the method constitutes the best practice. The information in the paper shall not be used without securing competent advice with respect to its suitability for any general or specific application, and assuming all liability arising from such use. The opinions, recommendations, findings, and conclusions do not necessarily reflect the views or policies of NIST or the United States Government.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 2 • June 2024
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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/.
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Received: Oct 12, 2023
Accepted: Dec 13, 2023
Published online: Mar 9, 2024
Published in print: Jun 1, 2024
Discussion open until: Aug 9, 2024
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