IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i2p590-d724787.html
   My bibliography  Save this article

Determinants of Demand Response Program Participation: Contingent Valuation Evidence from a Smart Thermostat Program

Author

Listed:
  • Jesse Kaczmarski

    (Department of Economics, The University of New Mexico, 1915 Roma Ave. NE 1019 ECON 1006E, Albuquerque, NM 87131, USA)

  • Benjamin Jones

    (Department of Economics, The University of New Mexico, 1915 Roma Ave. NE 1019 ECON 1006E, Albuquerque, NM 87131, USA)

  • Janie Chermak

    (Department of Economics, The University of New Mexico, 1915 Roma Ave. NE 1019 ECON 1006E, Albuquerque, NM 87131, USA)

Abstract

As renewable electricity generation continues to increase in the United States (US), considerable effort goes into matching heterogeneous supply to demand at a subhour time-step. As a result, some electric providers offer incentive-based programs for residential consumers that aim to reduce electric demand during high-demand periods. There is little research into determinants of consumer response to incentive-based programs beyond typical sociodemographic characteristics. To add to this body of literature, this paper presents the findings of a dichotomous choice contingent valuation (CV) survey targeting US ratepayers’ participation in a direct-load-control scheme utilizing a smart thermostat designed to reallocate consumer electricity demand on summer days when grid stress is high. Our results show approximately 50% of respondents are willing to participate at a median willingness-to-accept (WTA) figure of USD 9.50 (95% CI: 3.74, 15.25) per month that lasts for one summer (June through August)—or slightly less than USD 30 per annum. Participation is significantly affected by a respondent’s attitudes and preferences surrounding various environmental and institutional perspectives, but not by sociodemographic characteristics. These findings suggest utilities designing direct-load-control programs may improve participation by designing incentives specific to customers’ attitudes and preferences.

Suggested Citation

  • Jesse Kaczmarski & Benjamin Jones & Janie Chermak, 2022. "Determinants of Demand Response Program Participation: Contingent Valuation Evidence from a Smart Thermostat Program," Energies, MDPI, vol. 15(2), pages 1-18, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:590-:d:724787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/2/590/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/2/590/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    2. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    3. Frank A. Wolak, 2011. "Do Residential Customers Respond to Hourly Prices? Evidence from a Dynamic Pricing Experiment," American Economic Review, American Economic Association, vol. 101(3), pages 83-87, May.
    4. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    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. António Gomes Martins & Luís Pires Neves & José Luís Sousa, 2023. "Electricity Demand Side Management," Energies, MDPI, vol. 16(16), pages 1-3, August.
    2. Georgia K. Roberts & Dominique J. Pride & Joseph M. Little & Julie M. Mueller, 2023. "Willingness to Pay for Renewably-Sourced Home Heating in the Fairbanks North Star Borough," Energies, MDPI, vol. 16(8), pages 1-14, April.
    3. So-Yeon Park & Ju-Hee Kim & Jungkwan Seo & Seung-Hoon Yoo, 2022. "Evaluating the Economic Benefits of Tightening Regulations on the Use of Toluene, a Hazardous Chemical, in South Korea," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    4. Pourramezan, Ali & Samadi, Mahdi, 2023. "A system dynamics investigation on the long-term impacts of demand response in generation investment planning incorporating renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(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. Takanori Ida, Kayo Murakami, and Makoto Tanaka, 2016. "Electricity demand response in Japan: Experimental evidence from a residential photovoltaic power-generation system," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    2. Lang, Corey & Okwelum, Edson, 2015. "The mitigating effect of strategic behavior on the net benefits of a direct load control program," Energy Economics, Elsevier, vol. 49(C), pages 141-148.
    3. Ren'e Aid & Dylan Possamai & Nizar Touzi, 2018. "Optimal electricity demand response contracting with responsiveness incentives," Papers 1810.09063, arXiv.org, revised May 2019.
    4. Tatyana Deryugina & Alexander MacKay & Julian Reif, 2020. "The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation," American Economic Journal: Applied Economics, American Economic Association, vol. 12(1), pages 86-114, January.
    5. Makena Coffman & Paul Bernstein & Derek Stenclik & Sherilyn Wee & Aida Arik, 2018. "Integrating Renewable Energy with Time Varying Pricing," Working Papers 2018-6, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    6. Takanori Ida & Wenjie Wang, 2014. "A Field Experiment on Dynamic Electricity Pricing in Los Alamos:Opt-in Versus Opt-out," Discussion papers e-14-010, Graduate School of Economics Project Center, Kyoto University.
    7. Gilbert, Ben & Graff Zivin, Joshua, 2014. "Dynamic salience with intermittent billing: Evidence from smart electricity meters," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 176-190.
    8. Almas Heshmati, 2014. "Demand, Customer Base-Line And Demand Response In The Electricity Market: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 862-888, December.
    9. Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen & Frank A. Wolak, 2019. "Can Incentives to Increase Electricity Use Reduce the Cost of Integrating Renewable Resources," NBER Working Papers 25615, National Bureau of Economic Research, Inc.
    10. Takanori Ida & Kayo Murakami & Makoto Tanaka, 2015. "Electricity demand response in Japan:Experimental evidence from a residential photovoltaic generation system," Discussion papers e-15-006, Graduate School of Economics Project Center, Kyoto University.
    11. Miwa Nakai & Victor von Loessl & Heike Wetzel, 2022. "Preferences for dynamic electricity tariffs: A comparison of households in Germany and Japan," MAGKS Papers on Economics 202213, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    12. Ahmad Faruqui, Sanem Sergici, and Lamine Akaba, 2014. "The Impact of Dynamic Pricing on Residential and Small Commercial and Industrial Usage: New Experimental Evidence from Connecticut," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    13. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    14. Christian Gambardella & Michael Pahle & Wolf-Peter Schill, 2016. "Do Benefits from Dynamic Tariffing Rise? Welfare Effects of Real-Time Pricing under Carbon-Tax-Induced Variable Renewable Energy Supply," Discussion Papers of DIW Berlin 1621, DIW Berlin, German Institute for Economic Research.
    15. ITO Koichiro & IDA Takanori & TANAKA Makoto, 2015. "The Persistence of Moral Suasion and Economic Incentives: Field experimental evidence from energy demand," Discussion papers 15014, Research Institute of Economy, Trade and Industry (RIETI).
    16. Gambardella, Christian & Pahle, Michael, 2018. "Time-varying electricity pricing and consumer heterogeneity: Welfare and distributional effects with variable renewable supply," Energy Economics, Elsevier, vol. 76(C), pages 257-273.
    17. Kenneth Gillingham & David Rapson & Gernot Wagner, 2016. "The Rebound Effect and Energy Efficiency Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 68-88.
    18. Eri Nakamura & Fumitoshi Mizutani, 2019. "Necessary demand and extra demand of public utility product: identification using the stochastic frontier model," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 46(1), pages 45-64, March.
    19. Daniel Adelman & Canan Uçkun, 2019. "Dynamic Electricity Pricing to Smart Homes," Operations Research, INFORMS, vol. 67(6), pages 1520-1542, November.
    20. Freier, Julia & von Loessl, Victor, 2022. "Dynamic electricity tariffs: Designing reasonable pricing schemes for private households," Energy Economics, Elsevier, vol. 112(C).

    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:gam:jeners:v:15:y:2022:i:2:p:590-:d:724787. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.