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A Disaggregated Nonhomothetic Modeling of Responsiveness to Residential Time-of-Use Electricity Rates

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  • Mountain, Dean C
  • Lawson, Evelyn L

Abstract

In addition to quantifying the load impacts of time-differentiated rates on aggregate peak, off-peak groupings, a very finely disaggregated.Rotterdam demand system is described and estimated for explaining changes in detailed features of customers' electricity load patterns. This linear first difference formulation allows for nonhomotheticity, permits an examination of load impacts on critical hours of the week, and makes use of both control and time-of-use data. Moreover, the proposed specification is parameter parsimonious. An illustrative use of this model is portrayed through recent empirical evidence from a residential experiment of a northern winter-peaking utility in Ontario, Canada. Copyright 1992 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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  • Mountain, Dean C & Lawson, Evelyn L, 1992. "A Disaggregated Nonhomothetic Modeling of Responsiveness to Residential Time-of-Use Electricity Rates," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 181-207, February.
    • Handle: RePEc:ier:iecrev:v:33:y:1992:i:1:p:181-207
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    Cited by:

    1. Daruwala, Farhad & Denton, Frank T. & Mountain, Dean C., 2020. "One size may not fit all: Welfare benefits and cost reductions with optional differentiated household electricity rates," Resource and Energy Economics, Elsevier, vol. 61(C).
    2. Tarek Atalla & Simona Bigerna & Carlo Andrea Bollino, 2018. "Energy demand elasticities and weather worldwide," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(1), pages 207-237, April.
    3. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    4. Filippini, Massimo, 1995. "Electricity demand by time of use An application of the household AIDS model," Energy Economics, Elsevier, vol. 17(3), pages 197-204, July.
    5. Simona Bigerna and Carlo Andrea Bollino, 2015. "A System Of Hourly Demand in the Italian Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. Brännlund, Runar & Vesterberg, Mattias, 2021. "Peak and off-peak demand for electricity: Is there a potential for load shifting?," Energy Economics, Elsevier, vol. 102(C).
    7. Farhad Daruwala & Frank T. Denton & Dean C. Mountain, 2017. "One Size May Not Fit All: Welfare Benefits And Cost Reductions With Differentiated Household Electricity Rates In A General Equilibrium Model," Department of Economics Working Papers 2017-03, McMaster University.
    8. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
    9. Wai Choi & Anindya Sen & Adam White, 2011. "Response of industrial customers to hourly pricing in Ontario’s deregulated electricity market," Journal of Regulatory Economics, Springer, vol. 40(3), pages 303-323, December.
    10. Guo, Bowei & Weeks, Melvyn, 2022. "Dynamic tariffs, demand response, and regulation in retail electricity markets," Energy Economics, Elsevier, vol. 106(C).
    11. Hortay, Olivér & Szőke, Tamás, 2019. "Keresleti árrugalmasság becslése a magyar villamosenergia-piacon [Estimating demand-price elasticity on the Hungarian electric energy market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 788-804.
    12. Lijesen, Mark G., 2007. "The real-time price elasticity of electricity," Energy Economics, Elsevier, vol. 29(2), pages 249-258, March.

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