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Are vulnerable customers any different than their peers when exposed to critical peak pricing: Evidence from the U.S

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  • Cappers, Peter
  • Spurlock, C. Anna
  • Todd, Annika
  • Jin, Ling

Abstract

Recent broad-based deployment of Advanced Metering Infrastructure (AMI) enables the opportunity for broader adoption of time-based rates, and the benefits that result have been sizable contributors to making the investments cost effective. However, some stakeholders have raised concerns about the assumptions underlying the benefits assessments in AMI business cases. Such concerns are especially acute for certain subpopulations of residential customers. Low income, elderly and chronically ill (i.e., vulnerable) customers are believed to have less load that can be shifted or reduced to capture bill savings, lack the know-how or wherewithal with which to curtail usage, likely have more limited financial resources which may compel them to avoid high priced periods by reducing electricity for essential usage potentially causing them physical harm, and more generally may be more adversely affected by higher bills, which might possibly result from certain forms of time-based rates. There is very limited existing literature that addresses these questions specifically with regard to vulnerable subpopulations. This paper, based on a larger report, extends the existing empirical literature on the experiences of low-income customers exposed to critical peak pricing, and provides the first glimpses into the experiences of the elderly and those who reported being chronically ill.

Suggested Citation

  • Cappers, Peter & Spurlock, C. Anna & Todd, Annika & Jin, Ling, 2018. "Are vulnerable customers any different than their peers when exposed to critical peak pricing: Evidence from the U.S," Energy Policy, Elsevier, vol. 123(C), pages 421-432.
  • Handle: RePEc:eee:enepol:v:123:y:2018:i:c:p:421-432
    DOI: 10.1016/j.enpol.2018.09.013
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    References listed on IDEAS

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    1. Felder, Frank A., 2010. "The Practical Equity Implications of Advanced Metering Infrastructure," The Electricity Journal, Elsevier, vol. 23(6), pages 56-64, July.
    2. Brand, Stefanie A., 2010. "Dynamic Pricing for Residential Electric Customers: A Ratepayer Advocate's Perspective," The Electricity Journal, Elsevier, vol. 23(6), pages 50-55, July.
    3. Alexander, Barbara R., 2010. "Dynamic Pricing? Not So Fast! A Residential Consumer Perspective," The Electricity Journal, Elsevier, vol. 23(6), pages 39-49, July.
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    Cited by:

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    2. Gianluca Trotta & Kirsten Gram-Hanssen & Pernille Lykke Jørgensen, 2020. "Heterogeneity of Electricity Consumption Patterns in Vulnerable Households," Energies, MDPI, vol. 13(18), pages 1-17, September.
    3. Lei Zhang & Rui Tang, 2023. "Dispatch for a Continuous-Time Microgrid Based on a Modified Differential Evolution Algorithm," Mathematics, MDPI, vol. 11(2), pages 1-21, January.
    4. Zakeri, Behnam & Cross, Samuel & Dodds, Paul.E. & Gissey, Giorgio Castagneto, 2021. "Policy options for enhancing economic profitability of residential solar photovoltaic with battery energy storage," Applied Energy, Elsevier, vol. 290(C).
    5. Cappers, Peter A. & Todd-Blick, Annika, 2021. "Heterogeneity in own-price residential customer demand elasticities for electricity under time-of-use rates: Evidence from a randomized-control trial in the United States," Utilities Policy, Elsevier, vol. 73(C).

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