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Identifying and estimating the effects of a mandatory billing demand charge

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  • Öhrlund, Isak
  • Schultzberg, Mårten
  • Bartusch, Cajsa

Abstract

As peak demand for electricity continues to rise, distributors have begun charging small and medium-sized users for their short term demand rather than just their energy use. This is not only to meet the political aspirations for increased demand-side flexibility that now exist in many corners of the world, but to make sure that users are charged for the costs they incur. As it is only until recently that this type of users have come to face demand charges, there are however very few studies on what the actual effects of such pricing policies are, and those studies that do exist suffer from different methodological shortcomings that reduce their validity as a basis for real-world policy evaluations. This study provides the first state-of-the-art causal analysis of the demand response effects of a billing demand charge involuntarily introduced to small and medium sized users (35–63 A), using novel two-level time series models on retrospective observational consumption and survey data. Our analyses suggest that the tariff has induced an average response of −0.32 kWh/day per user over a two year long posttreatment period in comparison to a matched control group, equal to 7.4% of their daily average use during the pretreatment period. The response seems to have increased over time and to be greater during wintertime: around −0.70 kWh/day or 16.2% of the treated users’ average daily use during the pretreatment period. Comparing the individual users’ response to the size of their financial incentive to respond given the new tariff as well as their self-reported perception of the relative importance of electricity expenditures, we did not find any support for the common assumption that users with a higher financial incentive to respond do so to a greater extent. This might suggest that small and medium-sized commercial users, just as residential users, may exhibit non-financial drivers and barriers for engaging in demand response that may be vital to understand as policy makers and industry continue to seek increased demand-side flexibility.

Suggested Citation

  • Öhrlund, Isak & Schultzberg, Mårten & Bartusch, Cajsa, 2019. "Identifying and estimating the effects of a mandatory billing demand charge," Applied Energy, Elsevier, vol. 237(C), pages 885-895.
    • Handle: RePEc:eee:appene:v:237:y:2019:i:c:p:885-895
    DOI: 10.1016/j.apenergy.2019.01.028
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    1. Newsham, Guy R. & Birt, Benjamin J. & Rowlands, Ian H., 2011. "A comparison of four methods to evaluate the effect of a utility residential air-conditioner load control program on peak electricity use," Energy Policy, Elsevier, vol. 39(10), pages 6376-6389, October.
    2. Bartusch, Cajsa & Alvehag, Karin, 2014. "Further exploring the potential of residential demand response programs in electricity distribution," Applied Energy, Elsevier, vol. 125(C), pages 39-59.
    3. Davis, Alexander L. & Krishnamurti, Tamar & Fischhoff, Baruch & Bruine de Bruin, Wandi, 2013. "Setting a standard for electricity pilot studies," Energy Policy, Elsevier, vol. 62(C), pages 401-409.
    4. Thomas N. Taylor & Peter M. Schwarz, 1986. "A Residential Demand Charge: Evidence from the Duke Power Time-of-Day Pricing Experiment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 135-151.
    5. Thomas N. Taylor & Peter M. Schwarz, 1990. "The Long-Run Effects of a Time-of-Use Demand Charge," RAND Journal of Economics, The RAND Corporation, vol. 21(3), pages 431-445, Autumn.
    6. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    7. Ericson, Torgeir, 2011. "Households' self-selection of dynamic electricity tariffs," Applied Energy, Elsevier, vol. 88(7), pages 2541-2547, July.
    8. Ho, Daniel & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2011. "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i08).
    9. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
    10. Langlois-Bertrand, Simon & Pineau, Pierre-Olivier, 2018. "Pricing the transition: Empirical evidence on the evolution of electricity rate structures in North America," Energy Policy, Elsevier, vol. 117(C), pages 184-197.
    11. Bartusch, Cajsa & Wallin, Fredrik & Odlare, Monica & Vassileva, Iana & Wester, Lars, 2011. "Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception," Energy Policy, Elsevier, vol. 39(9), pages 5008-5025, September.
    12. Strengers, Yolande, 2010. "Air-conditioning Australian households: The impact of dynamic peak pricing," Energy Policy, Elsevier, vol. 38(11), pages 7312-7322, November.
    13. Niamh Murtagh & Birgitta Gatersleben & David Uzzell, 2014. "20∶60∶20 - Differences in Energy Behaviour and Conservation between and within Households with Electricity Monitors," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-12, March.
    14. Simshauser, Paul, 2016. "Distribution network prices and solar PV: Resolving rate instability and wealth transfers through demand tariffs," Energy Economics, Elsevier, vol. 54(C), pages 108-122.
    15. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
    16. Darby, Sarah J. & McKenna, Eoghan, 2012. "Social implications of residential demand response in cool temperate climates," Energy Policy, Elsevier, vol. 49(C), pages 759-769.
    17. Hu, Zheng & Kim, Jin-ho & Wang, Jianhui & Byrne, John, 2015. "Review of dynamic pricing programs in the U.S. and Europe: Status quo and policy recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 743-751.
    18. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
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    4. Qudrat-Ullah, Hassan & Kayal, Aymen & Mugumya, Andrew, 2021. "Cost-effective energy billing mechanisms for small and medium-scale industrial customers in Uganda," Energy, Elsevier, vol. 227(C).

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