IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v237y2019icp885-895.html
   My bibliography  Save this article

Identifying and estimating the effects of a mandatory billing demand charge

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919300285
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.01.028?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. van Zoest, Vera & El Gohary, Fouad & Ngai, Edith C.H. & Bartusch, Cajsa, 2021. "Demand charges and user flexibility – Exploring differences in electricity consumer types and load patterns within the Swedish commercial sector," Applied Energy, Elsevier, vol. 302(C).
    2. Lanot, Gauthier & Vesterberg, Mattias, 2021. "The price elasticity of electricity demand when marginal incentives are very large," Energy Economics, Elsevier, vol. 104(C).
    3. M. Hardmeier & A. Berthold & M. Siegrist, 2024. "Factors Influencing People’s Willingness to Shift Their Electricity Consumption," Journal of Consumer Policy, Springer, vol. 47(2), pages 199-221, June.
    4. da Silva, Roberto Perillo Barbosa & Quadros, Rodolfo & Shaker, Hamid Reza & da Silva, Luiz Carlos Pereira, 2020. "Effects of mixed electronic loads on the electrical energy systems considering different loading conditions with focus on power quality and billing issues," Applied Energy, Elsevier, vol. 277(C).
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Calver, Philippa & Simcock, Neil, 2021. "Demand response and energy justice: A critical overview of ethical risks and opportunities within digital, decentralised, and decarbonised futures," Energy Policy, Elsevier, vol. 151(C).
    2. Lanot, Gauthier & Vesterberg, Mattias, 2021. "The price elasticity of electricity demand when marginal incentives are very large," Energy Economics, Elsevier, vol. 104(C).
    3. Kobus, Charlotte B.A. & Klaassen, Elke A.M. & Mugge, Ruth & Schoormans, Jan P.L., 2015. "A real-life assessment on the effect of smart appliances for shifting households’ electricity demand," Applied Energy, Elsevier, vol. 147(C), pages 335-343.
    4. Dong, Jun & Jiang, Yuzheng & Liu, Dongran & Dou, Xihao & Liu, Yao & Peng, Shicheng, 2022. "Promoting dynamic pricing implementation considering policy incentives and electricity retailers’ behaviors: An evolutionary game model based on prospect theory," Energy Policy, Elsevier, vol. 167(C).
    5. Eid, Cherrelle & Codani, Paul & Perez, Yannick & Reneses, Javier & Hakvoort, Rudi, 2016. "Managing electric flexibility from Distributed Energy Resources: A review of incentives for market design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 237-247.
    6. Eid, Cherrelle & Koliou, Elta & Valles, Mercedes & Reneses, Javier & Hakvoort, Rudi, 2016. "Time-based pricing and electricity demand response: Existing barriers and next steps," Utilities Policy, Elsevier, vol. 40(C), pages 15-25.
    7. Srivastava, Aman & Van Passel, Steven & Kessels, Roselinde & Valkering, Pieter & Laes, Erik, 2020. "Reducing winter peaks in electricity consumption: A choice experiment to structure demand response programs," Energy Policy, Elsevier, vol. 137(C).
    8. Bartusch, Cajsa & Juslin, Peter & Stikvoort, Britt & Yang-Wallentin, Fan & Öhrlund, Isak, 2024. "Opening the black box of demand response: Exploring the cognitive processes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    9. Yilmaz, Selin & Xu, Xiaojing & Cabrera, Daniel & Chanez, Cédric & Cuony, Peter & Patel, Martin K., 2020. "Analysis of demand-side response preferences regarding electricity tariffs and direct load control: Key findings from a Swiss survey," Energy, Elsevier, vol. 212(C).
    10. 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.
    11. Srivastava, A. & Van Passel, S. & Valkering, P. & Laes, E.J.W., 2021. "Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    12. Andre Rossi Oliveira, 2024. "Evaluating the Short-term Causal Effect of Early Alert on Student Performance," Research in Higher Education, Springer;Association for Institutional Research, vol. 65(7), pages 1395-1419, November.
    13. Cortés-Arcos, Tomás & Bernal-Agustín, José L. & Dufo-López, Rodolfo & Lujano-Rojas, Juan M. & Contreras, Javier, 2017. "Multi-objective demand response to real-time prices (RTP) using a task scheduling methodology," Energy, Elsevier, vol. 138(C), pages 19-31.
    14. Buckley, Penelope, 2020. "Prices, information and nudges for residential electricity conservation: A meta-analysis," Ecological Economics, Elsevier, vol. 172(C).
    15. Francesco Liberati & Alessandro Di Giorgio, 2017. "Economic Model Predictive and Feedback Control of a Smart Grid Prosumer Node," Energies, MDPI, vol. 11(1), pages 1-23, December.
    16. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    17. Passey, Robert & Haghdadi, Navid & Bruce, Anna & MacGill, Iain, 2017. "Designing more cost reflective electricity network tariffs with demand charges," Energy Policy, Elsevier, vol. 109(C), pages 642-649.
    18. Dütschke, Elisabeth & Paetz, Alexandra-Gwyn, 2013. "Dynamic electricity pricing—Which programs do consumers prefer?," Energy Policy, Elsevier, vol. 59(C), pages 226-234.
    19. Klaassen, E.A.M. & Kobus, C.B.A. & Frunt, J. & Slootweg, J.G., 2016. "Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands," Applied Energy, Elsevier, vol. 183(C), pages 1065-1074.
    20. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:237:y:2019:i:c:p:885-895. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.