Electric utility valuations of investments to reduce the risks of long-duration, widespread power interruptions, part I: Background

References

• Anderson, K., Li, X., Dalvi, S., Ericson, S., Barrows, C., Murphy, C., & Hotchkiss, E. (2019). Integrating the value of electricity resilience in energy planning and operations decisions. IEEE Systems Journal, DOI https://doi.org/10.1109/JSYST.2019.2961298.
   Google Scholar
• Baik, S., Sirinterlikci, S., Park, J. W., Davis, A., Morgan, M. G. , et al. (2019). Estimating residential customers’ costs of large, long duration blackouts. In P.H. Larsen, Sanstad, A.H., LaCommare, K.H., Eto, J.H. (Eds.), Frontiers in the Economics of Widespread Long-Duration Power Interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory.
   Google Scholar
• Boero, R., & Edwards, B. (2017). Hurricane sandy economics impact assessment: A computable general equilibrium approach and validation. Los Alamos National Laboratory Report LA-UR-17-27053. Los Alamos, NM: Los Alamos National Laboratory.
   Google Scholar
• California Department of Forestry and Fire Protection (CAL FIRE). (2019a). Top 20 Largest California Wildfires. Table.
   Google Scholar
• California Department of Forestry and Fire Protection (CAL FIRE). (2019b.) Top 20 Most Destructive California Wildfires. Table.
   Google Scholar
• Campbell, R. (2012). Weather-related power outages and electric system resiliency. (Report R42696). U.S. Congressional Research Service.
   Google Scholar
• Costello, K. (2018). Challenges surrounding electric power resiliency. Public Utilities Fortnightly, 84–91. https://www.fortnightly.com/fortnightly/2018/04/challenges-surrounding-electric-power-resiliency
   Google Scholar
• Executive Office of the President (EOP). (2013b). Draft report to congress on the benefits and costs of federal regulations. The White House.
   Google Scholar
• Executive Office of the President of the United States. (EOP). (2013a). Economic benefits of increasing electric grid resilience to weather outages. The White House.
   Google Scholar
• Eyer, J., Rose, A. (2019). Mitigation and resilience tradeoffs in electricity outages. In P. H. Larsen, Sanstad, A.H., LaCommare, K.H., Eto, J.H. (Eds.), Frontiers in the economics of widespread long-duration power interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory.
   Google Scholar
• Fang, Y., & Sansavini, G. (2017). Optimizing power system investments and resilience against attacks. Reliability Engineering and System Safety, 159, 161–173. https://doi.org/10.1016/j.ress.2016.10.028
   Web of Science ®Google Scholar
• Finster, M., Philips, J., & Wallace, K. (2016). Front-line resilience perspectives: The electric grid. Global Security Sciences Division, Argonne National Laboratory, Report ANL/GSS-16/2.
   Google Scholar
• Greenberg, M., Mantell, N., Lahr, M., Felder, F., & Zimmerman, R. (2007). Short and intermediate economic impacts of a terrorist-initiated loss of electric power: Case study of New Jersey. Energy Policy, 35(1), 722–733. https://doi.org/10.1016/j.enpol.2006.01.017
   Web of Science ®Google Scholar
• Grid Modernization Laboratory Consortium (GMLC). (2017). Grid modernization: Metrics analysis (GMLC 1.1). Pacific Northwest National Laboratory Report 26541. https://gridmod.labworks.org/sites/default/files/resources/GMLC1%201_Reference_Manual_2%201_final_2017_06_01_v4_wPNNLNo_1.pdf
   Google Scholar
• Institute of Electrical and Electronics Engineers (IEEE). (2020). Resilience framework, methods, and metrics for the electricity sector. IEEE Power & Energy Society Technical Report PES-TR83.
   Google Scholar
• Keogh, M., & Cody, C. (2013). Resilience in Regulated Utilities. The National Association of Regulatory Utility Commissioners (NARUC). http://www.ncsl.org/Portals/1/Documents/forum/Forum_2014/ResilienceRegulatedUtilities.pdf
   Google Scholar
• Kwasinski, A. (2016). Quantitative model and metrics of electrical grids’ resilience evaluated at a power distribution level. Energies, 9(2), 93. https://doi.org/10.3390/en9020093
   Web of Science ®Google Scholar
• LaCommare, K., & Eto, J. (2004). Understanding the cost of power interruptions to US electricity consumers. Lawrence Berkeley National Laboratory.
   Google Scholar
• LaCommare, K., & Eto, J. (2006). Cost of power interruptions to electricity consumers in the United States (US). Energy, 31(12), 1845–1855. https://doi.org/10.1016/j.energy.2006.02.008
   Web of Science ®Google Scholar
• LaCommare, K. H., Eto, J. H., Dunn, L. N., & Sohn, M. D. (2018). Improving the estimated cost of sustained power interruptions to electricity customers. Energy, 153, 1038–1047. https://doi.org/10.1016/j.energy.2018.04.082
   Web of Science ®Google Scholar
• LaCommare, K. H., Larsen, P., & Eto, J. (2017). Evaluating proposed investments in power system reliability and resilience: Preliminary results from interviews with public utility commission staff. Lawrence Berkeley National Laboratory, January.
   Google Scholar
• Larsen, P. H. (2016). A method to estimate the costs and benefits of undergrounding electricity transmission and distribution lines. Energy Economics, 60, 47–61. http://dx.doi.org/10.1016/j.eneco.2016.09.011
   Web of Science ®Google Scholar
• Larsen, P., B. Boehlert, J. Eto, K. Hamachi-LaCommare, J. Martinich, and L. Rennels. 2018. Projecting future costs to U.S. electric utility customers from power interruptions. Energy, 147, 1256–1277. https://doi.org/10.1016/j.energy.2017.12.081
   PubMed Web of Science ®Google Scholar
• Larsen, P., Sanstad, A. H., LaCommare, K. H., & Eto, J. H . 2019). Frontiers in the economics of widespread long-duration power interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory. https://eta-publications.lbl.gov/sites/default/files/long_duration_interruptions_workshop_proceedings.pdf
   Google Scholar
• Maliszewski, P. J., & Perrings, C. (2012). Factors in the resilience of electrical power distribution infrastructures. Applied Geography, 32(2), 668–679. https://doi.org/10.1016/j.apgeog.2011.08.001
   Web of Science ®Google Scholar
• Morrissey, K., Plater, A., & Dean, M. (2018). The cost of electric power outages in the residential sector: A willingness to pay approach. Applied Energy, 212, 141–150. https://doi.org/10.1016/j.apenergy.2017.12.007
   Web of Science ®Google Scholar
• National Academies of Sciences (NAS), Engineering, and Medicine. (2017). Enhancing the resilience of the Nation’s electricity system. Washington, DC: National Academies Press. https://doi.org/10.17226/24836
   Google Scholar
• National Association of Regulatory Utility Commissions and Converge Strategies LLC (NARUC/Converge). (2019). The value of resilience for distributed energy resources: An overview of current analytical practices.
   Google Scholar
• National Association of Regulatory Utility Commissions and Converge Strategies LLC (NARUC/Converge). (2021). Regulatory considerations for utility investments in defense energy resilience.
   Google Scholar
• NHC. January. 2018. Costliest U.S. tropical cyclones tables updated. Miami, FL: U.S. National Hurricane Center (NHC).
   Google Scholar
• Pierre, B. J., Arguello, B., Staid, A., & Guttromson, R. T. Investment optimization to improve power system resilience. 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), IEEE.
   Google Scholar
• The President’s National Infrastructure Advisory Council (NIAC). (2018). Surviving a Catastrophic Power Outage. https://www.dhs.gov/sites/default/files/publications/NIAC%20Catastrophic%20Power%20Outage%20Study_508%20FINAL.pdf
   Google Scholar
• Primen/EPRI. (2001). The cost of power disturbances to industrial and digital economy companies.
   Google Scholar
• Richter, -L.-L., & Weeks, M. (2016). Flexible mixed logit with posterior analysis: exploring willingness-to-pay for grid resilience. Cambridge Working Papers in Economics 1631, Faculty of Economics, University of Cambridge.
   Google Scholar
• Rickerson, W., Wu, M., & Pringle, M. (2018). Beyond the Fence Line: Strengthening military capabilities through energy resilience partnerships. Washington, DC: Association of Defense Communities.
   Google Scholar
• Rosales-Asensio, E., de Simon-Martin, M., Rosales, A. E., & Colmenar-Santos, A. (2021). Solar-plus-storage benefits for end-users placed at radial and meshed grids: An economic and resiliency analysis. International Journal of Electrical Power and Energy Systems, 128, 106675. https://doi.org/10.1016/j.ijepes.2020.106675
   Web of Science ®Google Scholar
• Rose, A., Benavides, J., Chang, S. E., Szczesniak, P., & Lim, D. (1997). The regional economic impact of an earthquake: direct and indirect effects of electricity lifeline disruptions. Journal of Regional Science, 37(3), 437–458. https://doi.org/10.1111/0022-4146.00063
   Web of Science ®Google Scholar
• Rose, A., Oladosu, G., & Salvino, D. 2005). Economic impacts of electricity outages in Los Angeles: The importance of resilience and general equilibrium effects. In M. A. Crew & M. Spiegel (Eds.), Obtaining the best from regulation and competition, Vol.47. (pp. 179-211). Springer Science.
   Google Scholar
• Sagebiel, J. (2017). Preference heterogeneity in energy discrete choice experiments: A review on methods for model selection. Renewable and Sustainable Energy Reviews, 69, 804–811. https://doi.org/10.1016/j.rser.2016.11.138
   Web of Science ®Google Scholar
• Sanstad, A. H. (2016). Regional economic modeling of electricity supply disruptions: A review and recommendations for research; Lawrence Berkeley National Laboratory Report LBNL-1004426.
   Google Scholar
• Sanstad, A. H., Zhu, Q., Leibowicz, B. D., Larsen, P. H., & Eto, J. H. (2020). Case studies of the economic impacts of power interruptions and damage to electricity system infrastructure from extreme events. Lawrence Berkeley National Laboratory report.
   Google Scholar
• Schellenberg, J., Collins, M., Sullivan, M., Hees, S., Bieler, S. (2019). Data landscape: Challenges and opportunities. In P. H. Larsen, Sanstad, A.H., LaCommare, K.H., Eto, J.H. (Eds,). Frontiers in the economics of widespread long-duration power interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory.
   Google Scholar
• Shawhan, D. 2019). Using stated preferences to estimate the value of avoiding power outages: A commentary with input from six continents. In P. H. Larsen, Sanstad, A.H., LaCommare, K.H., Eto, J.H. (Eds.), Frontiers in the economics of widespread long-duration power interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory.
   Google Scholar
• Shen, L., Tang, Y., & Tang, L. (2021). Understanding key factors affecting power systems resilience. Reliability Engineering and System Safety, 212, 107621. https://doi.org/10.1016/j.ress.2021.107621
   Web of Science ®Google Scholar
• Stockton, P. (2014). Resilience for Black Sky Days. The National Association of Regulatory Utility Commissioners (NARUC).
   Google Scholar
• Sue Wing, I., Rose, A. Z. (2019). Economic consequences of electric power infrastructure disruptions: an analytical general equilibrium model. In P. H. Larsen, Sanstad, A.H., LaCommare, K.H., Eto, J.H., (Eds.), Frontiers in the economics of widespread long-duration power interruptions. Berkeley, CA: Lawrence Berkeley National Laboratory.
   Google Scholar
• Sue Wing, I., & Rose, A. Z. (2020). Economic consequence analysis of electric power infrastructure disruptions: General equilibrium approaches. Energy Economics, 89, 104756. https://doi.org/10.1016/j.eneco.2020.104756
   Web of Science ®Google Scholar
• Sullivan, M., Collins, M. T., Schellenberg, J., & Larsen, P. H. (2018). Estimating power system interruption costs - A guidebook for electric utilities. Lawrence Berkeley National Laboratory.
   Google Scholar
• Sullivan, M., Mercurio, J. M., & Schellenberg, J. (2009). Estimated values of service reliability for electric utility customers in the United States. Berkeley, CA: Lawrence Berkeley National Laboratory Report LBNL-2132E.
   Google Scholar
• Sullivan, M., Schellenberg, J., & Blundell, M. (2015). Updated value of service reliability estimates for electric utility customers in the United States. Berkeley, CA: Lawrence Berkeley National Laboratory Report LBNL-6941E.
   Google Scholar
• Swaminathan, S., & Sen, R. (1998). Review of power quality applications of energy storage systems. Sandia National Laboratory.
   Google Scholar
• United States Government Accountability Office (GAO). (2014). Climate change – energy infrastructure risks and adaptation efforts. Report to Congressional Requestors, GAO-14-74.
   Google Scholar
• U. S. Department of Energy (DOE). (2010). Hardening and Resiliency U.S. Energy Industry Response to Recent Hurricane Seasons. https://www.oe.netl.doe.gov/docs/HR-Report-final-081710.pdf
   Google Scholar
• U. S. Department of Energy (DOE). (2013). Comparing the Impacts of Northeast Hurricanes on Energy Infrastructure. https://www.energy.gov/sites/prod/files/2013/04/f0/Northeast%20Storm%20Comparison_FINAL_041513b.pdf
   Google Scholar
• U. S. Department of Energy (DOE). (2015). Climate Change and the U.S. Energy Sector: Regional Vulnerabilities and Resilience Solutions. http://energy.gov/sites/prod/files/2015/10/f27/Regional_Climate_Vulnerabilities_and_Resilience_Solutions_0.pdf
   Google Scholar
• U. S. Department of Energy (DOE). (2016). Climate Change and the U.S. Energy Sector: Guide for Climate Change Resilience Planning. U.S. Department of Energy. https://www.energy.gov/sites/prod/files/2016/10/f33/Climate%20Change%20and%20the%20Electricity%20Sector%20Guide%20for%20Climate%20Change%20Resilience%20Planning%20September%202016_0.pdf
   Google Scholar
• U.S. Department of Energy (DOE). (2017). Transforming the Nation’s Electricity Sector: The Second Installment of the Quadrennial Energy Review (QER). https://www.energy.gov/sites/prod/files/2017/01/f34/Chapter%20IV%20Ensuring%20Electricity%20System%20Reliability%2C%20Security%2C%20and%20Resilience.pdf
   Google Scholar
• U. S. Global Climate Research Program (USGCRP). (2017). Climate science special report: fourth national climate assessment, Volume I; D. J. Wuebbles, D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, & T. K. Maycock, Eds., pp. 470. U.S. Global ChangeResearch Program.
   Google Scholar
• Zamuda, C., Larsen, P., Collins, M., Bieler, S., Bieler, S., & Hees, S. (2019). Monetization methods for evaluating investments in electricity system resilience to extreme weather and climate change. The Electricity Journal, 32(9), 106641. https://doi.org/10.1016/j.tej.2019.106641
   Google Scholar