IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i10p2795-d553616.html
   My bibliography  Save this article

Shedding Light on the Factors That Influence Residential Demand Response in Japan

Author

Listed:
  • Nikolaos Iliopoulos

    (Graduate Program in Sustainability Science–Global Leadership Initiative, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa City 277-8563, Japan)

  • Motoharu Onuki

    (Graduate Program in Sustainability Science–Global Leadership Initiative, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa City 277-8563, Japan)

  • Miguel Esteban

    (Faculty of Civil and Environmental Engineering, Waseda University, 60-106, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan)

Abstract

Residential demand response empowers the role of electricity consumers by allowing them to change their patterns of consumption, which can help balance the energy grid. Although such type of management is envisaged to play an increasingly important role in the integration of renewables into the grid, the factors that influence household engagement in these initiatives have not been fully explored in Japan. This study examines the influence of interpersonal, intrapersonal, and socio-demographic characteristics of households in Yokohama on their willingness to participate in demand response programs. Time of use, real time pricing, critical peak pricing, and direct load control were considered as potential candidates for adoption. In addition, the authors explored the willingness of households to receive non-electricity related information in their in-home displays and participate in a philanthropy-based peer-to-peer energy platform. Primary data were collected though a questionnaire survey and supplemented by key informant interviews. The findings indicate that household income, ownership of electric vehicles, socio-environmental awareness, perceived sense of comfort, control, and complexity, as well as philanthropic inclinations, all constitute drivers that influence demand flexibility. Finally, policy recommendations that could potentially help introduce residential demand response programs to a wider section of the public are also proposed.

Suggested Citation

  • Nikolaos Iliopoulos & Motoharu Onuki & Miguel Esteban, 2021. "Shedding Light on the Factors That Influence Residential Demand Response in Japan," Energies, MDPI, vol. 14(10), pages 1-23, May.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2795-:d:553616
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/10/2795/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/10/2795/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Euan Phimister, Esperanza Vera-Toscano and Deborah Roberts, 2015. "The Dynamics of Energy Poverty: Evidence from Spain," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    2. Barr, Stewart & Gilg, Andrew W & Ford, Nicholas, 2005. "The household energy gap: examining the divide between habitual- and purchase-related conservation behaviours," Energy Policy, Elsevier, vol. 33(11), pages 1425-1444, July.
    3. Lopes, Marta A.R. & Henggeler Antunes, Carlos & Janda, Kathryn B. & Peixoto, Paulo & Martins, Nelson, 2016. "The potential of energy behaviours in a smart(er) grid: Policy implications from a Portuguese exploratory study," Energy Policy, Elsevier, vol. 90(C), pages 233-245.
    4. Chatzigeorgiou, I.M. & Andreou, G.T., 2021. "A systematic review on feedback research for residential energy behavior change through mobile and web interfaces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Schultz, P. Wesley & Estrada, Mica & Schmitt, Joseph & Sokoloski, Rebecca & Silva-Send, Nilmini, 2015. "Using in-home displays to provide smart meter feedback about household electricity consumption: A randomized control trial comparing kilowatts, cost, and social norms," Energy, Elsevier, vol. 90(P1), pages 351-358.
    6. Ben-Haim, Yakov, 2021. "Feedback for energy conservation: An info-gap approach," Energy, Elsevier, vol. 223(C).
    7. Bradley, Peter & Coke, Alexia & Leach, Matthew, 2016. "Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider," Energy Policy, Elsevier, vol. 98(C), pages 108-120.
    8. Ying Han & Jianhua Shi & Yuanfan Yang & Yaxin Wang, 2019. "Direct Rebound Effect for Electricity Consumption of Urban Residents in China Based on the Spatial Spillover Effect," Energies, MDPI, vol. 12(11), pages 1-16, May.
    9. Cosmo, Valeria Di & O’Hora, Denis, 2017. "Nudging electricity consumption using TOU pricing and feedback: evidence from Irish households," Journal of Economic Psychology, Elsevier, vol. 61(C), pages 1-14.
    10. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    11. Ek, Kristina & Söderholm, Patrik, 2010. "The devil is in the details: Household electricity saving behavior and the role of information," Energy Policy, Elsevier, vol. 38(3), pages 1578-1587, March.
    12. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    13. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
    14. Gyamfi, Samuel & Krumdieck, Susan & Urmee, Tania, 2013. "Residential peak electricity demand response—Highlights of some behavioural issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 71-77.
    15. Druckman, A. & Jackson, T., 2008. "Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model," Energy Policy, Elsevier, vol. 36(8), pages 3167-3182, August.
    16. Buchanan, Kathryn & Banks, Nick & Preston, Ian & Russo, Riccardo, 2016. "The British public’s perception of the UK smart metering initiative: Threats and opportunities," Energy Policy, Elsevier, vol. 91(C), pages 87-97.
    17. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    18. Smith, Alexander M. & Brown, Marilyn A., 2015. "Demand response: A carbon-neutral resource?," Energy, Elsevier, vol. 85(C), pages 10-22.
    19. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    20. Wallis, Hannah & Nachreiner, Malte & Matthies, Ellen, 2016. "Adolescents and electricity consumption; Investigating sociodemographic, economic, and behavioural influences on electricity consumption in households," Energy Policy, Elsevier, vol. 94(C), pages 224-234.
    21. Hafner, Rebecca J. & Elmes, David & Read, Daniel, 2019. "Promoting behavioural change to reduce thermal energy demand in households: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 205-214.
    22. Horne, Christine & Kennedy, Emily Huddart, 2017. "The power of social norms for reducing and shifting electricity use," Energy Policy, Elsevier, vol. 107(C), pages 43-52.
    23. Luciano De Castro, 2011. "The Economics of the Smart Grid," Discussion Papers 1544, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    24. Batalla-Bejerano, Joan & Trujillo-Baute, Elisa & Villa-Arrieta, Manuel, 2020. "Smart meters and consumer behaviour: Insights from the empirical literature," Energy Policy, Elsevier, vol. 144(C).
    25. Morris, Peter & Vine, Desley & Buys, Laurie, 2015. "Application of a Bayesian Network complex system model to a successful community electricity demand reduction program," Energy, Elsevier, vol. 84(C), pages 63-74.
    26. Hall, Nina L. & Jeanneret, Talia D. & Rai, Alan, 2016. "Cost-reflective electricity pricing: Consumer preferences and perceptions," Energy Policy, Elsevier, vol. 95(C), pages 62-72.
    27. Thomas Morstyn & Niall Farrell & Sarah J. Darby & Malcolm D. McCulloch, 2018. "Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants," Nature Energy, Nature, vol. 3(2), pages 94-101, February.
    28. repec:aen:journl:eeep4_1_phimister is not listed on IDEAS
    29. Gilbraith, Nathaniel & Powers, Susan E., 2013. "Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City," Energy Policy, Elsevier, vol. 59(C), pages 459-469.
    30. Parrish, Bryony & Heptonstall, Phil & Gross, Rob & Sovacool, Benjamin K., 2020. "A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response," Energy Policy, Elsevier, vol. 138(C).
    31. Iliopoulos, Nikolaos & Esteban, Miguel & Kudo, Shogo, 2020. "Assessing the willingness of residential electricity consumers to adopt demand side management and distributed energy resources: A case study on the Japanese market," Energy Policy, Elsevier, vol. 137(C).
    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. Qi Huang & Aihua Jiang & Yu Zeng & Jianan Xu, 2022. "Community Flexible Load Dispatching Model Based on Herd Mentality," Energies, MDPI, vol. 15(13), pages 1-18, June.
    2. Sabina Kordana-Obuch & Mariusz Starzec & Daniel Słyś, 2021. "Assessment of the Feasibility of Implementing Shower Heat Exchangers in Residential Buildings Based on Users’ Energy Saving Preferences," Energies, MDPI, vol. 14(17), pages 1-30, September.

    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. Parrish, Bryony & Heptonstall, Phil & Gross, Rob & Sovacool, Benjamin K., 2020. "A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response," Energy Policy, Elsevier, vol. 138(C).
    2. Sloot, Daniel & Scheibehenne, Benjamin, 2022. "Understanding the financial incentive conundrum: A meta-analysis of the effectiveness of financial incentive interventions in promoting energy conservation behavior," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Nilsson, Anders & Lazarevic, David & Brandt, Nils & Kordas, Olga, 2018. "Household responsiveness to residential demand response strategies: Results and policy implications from a Swedish field study," Energy Policy, Elsevier, vol. 122(C), pages 273-286.
    4. Dana Abi Ghanem & Tracey Crosbie, 2021. "The Transition to Clean Energy: Are People Living in Island Communities Ready for Smart Grids and Demand Response?," Energies, MDPI, vol. 14(19), pages 1-26, September.
    5. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    6. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
    7. Sridhar, Araavind & Honkapuro, Samuli & Ruiz, Fredy & Stoklasa, Jan & Annala, Salla & Wolff, Annika & Rautiainen, Antti, 2023. "Residential consumer preferences to demand response: Analysis of different motivators to enroll in direct load control demand response," Energy Policy, Elsevier, vol. 173(C).
    8. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
    9. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    10. Heshmati, Almas, 2012. "Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market," IZA Discussion Papers 6637, Institute of Labor Economics (IZA).
    11. 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.
    12. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    13. Fettermann, Diego Castro & Cavalcante, Caroline Gobbo Sá & Ayala, Néstor Fabián & Avalone, Marianne Costa, 2020. "Configuration of a smart meter for Brazilian customers," Energy Policy, Elsevier, vol. 139(C).
    14. Bastida, Leire & Cohen, Jed J. & Kollmann, Andrea & Moya, Ana & Reichl, Johannes, 2019. "Exploring the role of ICT on household behavioural energy efficiency to mitigate global warming," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 455-462.
    15. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    16. Batalla-Bejerano, Joan & Trujillo-Baute, Elisa & Villa-Arrieta, Manuel, 2020. "Smart meters and consumer behaviour: Insights from the empirical literature," Energy Policy, Elsevier, vol. 144(C).
    17. Smith, Alexander M. & Brown, Marilyn A., 2015. "Demand response: A carbon-neutral resource?," Energy, Elsevier, vol. 85(C), pages 10-22.
    18. 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.
    19. Li, Xin & Chen, Hsing Hung & Tao, Xiangnan, 2016. "Pricing and capacity allocation in renewable energy," Applied Energy, Elsevier, vol. 179(C), pages 1097-1105.
    20. Mi, Lingyun & Gan, Xiaoli & Sun, Yuhuan & Lv, Tao & Qiao, Lijie & Xu, Ting, 2021. "Effects of monetary and nonmonetary interventions on energy conservation: A meta-analysis of experimental studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(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:14:y:2021:i:10:p:2795-:d:553616. 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.