IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v400y2025ics0306261925013194.html

Quantification of rural residents' willingness for electricity demand response: Insights from field simulation experiments

Author

Listed:
  • Zhou, Tingting
  • Luo, Xi
  • Liu, Xiaojun
  • Liu, Guangchuan
  • He, Lin
  • Zhai, Xiongxiong
  • Wang, Gang
  • Gao, Xiaoxiao

Abstract

Owing to the lack of effective methods for collecting data on rural residents' willingness to participate in electricity demand response (EDR), it is difficult to accurately assess the electricity demand potential in rural areas and ensure the rationality of EDR policy formulation. Hence, this study developed a questionnaire survey method equipped with on-site simulation to accurately gather data on rural residents' willingness to adjust their usage of controllable household appliances. Furthermore, a comprehensive index system considering the stages of cognition, understanding, and acceptance was developed to evaluate rural residents' willingness to participate in EDR, and a binary probit model was then used to analyse the factors driving rural residents' willingness to participate in EDR. Results indicated that (1) approximately 95 % of rural residents demonstrated potential willingness to participate in EDR, manifesting in four distinct types, namely, cautious participation, proactive response, selective participation, and balanced participation. The proactive response group accounted for the largest proportion of participants (36.39 %). (2) Rural residents preferred to adjust electricity usage for scooters or air conditioners individually, but tended to operate washing machines with other appliances simultaneously. (3) Although simultaneously adjusting several appliances could reduce the electricity bill by as much as 28.78 %, the proportion of participants willing to choose this type of adjustment was the lowest (19 %). (4) Education level and occupation were the key factors affecting rural residents' willingness to participate in EDR.

Suggested Citation

  • Zhou, Tingting & Luo, Xi & Liu, Xiaojun & Liu, Guangchuan & He, Lin & Zhai, Xiongxiong & Wang, Gang & Gao, Xiaoxiao, 2025. "Quantification of rural residents' willingness for electricity demand response: Insights from field simulation experiments," Applied Energy, Elsevier, vol. 400(C).
    • Handle: RePEc:eee:appene:v:400:y:2025:i:c:s0306261925013194
    DOI: 10.1016/j.apenergy.2025.126589
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925013194
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.126589?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Bo & Deng, Nana & Li, Haoxiang & Zhao, Wenhui & Liu, Jie & Wang, Zhaohua, 2021. "Effect and mechanism of monetary incentives and moral suasion on residential peak-hour electricity usage," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Dinh, Huy Truong & Lee, Kyu-haeng & Kim, Daehee, 2022. "Supervised-learning-based hour-ahead demand response for a behavior-based home energy management system approximating MILP optimization," Applied Energy, Elsevier, vol. 321(C).
    3. Qiu, Yueming & Colson, Gregory & Wetzstein, Michael E., 2017. "Risk preference and adverse selection for participation in time-of-use electricity pricing programs," Resource and Energy Economics, Elsevier, vol. 47(C), pages 126-142.
    4. Shuchen Cong & Destenie Nock & Yueming Lucy Qiu & Bo Xing, 2022. "Unveiling hidden energy poverty using the energy equity gap," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. Wang, Zhaohua & Zhao, Wenhui & Deng, Nana & Zhang, Bin & Wang, Bo, 2021. "Mixed data-driven decision-making in demand response management: An empirical evidence from dynamic time-warping based nonparametric-matching DID," Omega, Elsevier, vol. 100(C).
    6. Kim, Jihyo & Lee, Soomin & Jang, Heesun, 2022. "Lessons from residential electricity demand analysis on the time of use pricing experiment in South Korea," Energy Economics, Elsevier, vol. 113(C).
    7. Wang, Zhaohua & Li, Hao & Deng, Nana & Cheng, Kaiwei & Lu, Bin & Zhang, Bin & Wang, Bo, 2020. "How to effectively implement an incentive-based residential electricity demand response policy? Experience from large-scale trials and matching questionnaires," Energy Policy, Elsevier, vol. 141(C).
    8. Yan, Aqian & Luo, Xiaofeng & Zhang, Junbiao & Tang, Lin, 2024. "Does internet use promote clean energy use for cooking by women-headed rural households in China?," Utilities Policy, Elsevier, vol. 86(C).
    9. Zhaohua Wang & Bin Lu & Bo Wang & Yueming (Lucy) Qiu & Han Shi & Bin Zhang & Jingyun Li & Hao Li & Wenhui Zhao, 2023. "Incentive based emergency demand response effectively reduces peak load during heatwave without harm to vulnerable groups," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    10. Sridhar, Araavind & Honkapuro, Samuli & Ruiz, Fredy & Stoklasa, Jan & Annala, Salla & Wolff, Annika & Rautiainen, Antti, 2023. "Toward residential flexibility—Consumer willingness to enroll household loads in demand response," Applied Energy, Elsevier, vol. 342(C).
    11. Alasseri, Rajeev & Rao, T. Joji & Sreekanth, K.J., 2020. "Institution of incentive-based demand response programs and prospective policy assessments for a subsidized electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    12. Balasubramanian, S. & Balachandra, P., 2021. "Effectiveness of demand response in achieving supply-demand matching in a renewables dominated electricity system: A modelling approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    13. 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).
    14. Yin, Guangzhi & Duan, Maosheng, 2022. "Pricing the deep peak regulation service of coal-fired power plants to promote renewable energy integration," Applied Energy, Elsevier, vol. 321(C).
    15. 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).
    16. Wang, Bo & Yang, Zihan & Le Hoa Pham, Thi & Deng, Nana & Du, Heran, 2023. "Can social impacts promote residents’ pro-environmental intentions and behaviour: Evidence from large-scale demand response experiment in China," Applied Energy, Elsevier, vol. 340(C).
    17. Schlereth, Christian & Skiera, Bernd & Schulz, Fabian, 2018. "Why do consumers prefer static instead of dynamic pricing plans? An empirical study for a better understanding of the low preferences for time-variant pricing plans," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1165-1179.
    18. Singer, Hilal & Özşahin, Şükrü, 2024. "An interval-valued intuitionistic fuzzy analytic hierarchy process model for understanding consumer decision-making in non-wood forest product purchases," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    19. Xu, Shuling & Yang, Zihan & Deng, Nana & Wang, Bo, 2024. "Residents' willingness to be compensated for power rationing during peak hours based on choice experiment," Applied Energy, Elsevier, vol. 367(C).
    20. Tayal, Dev & Evers, Uwana, 2018. "Consumer preferences and electricity pricing reform in Western Australia," Utilities Policy, Elsevier, vol. 54(C), pages 115-124.
    21. 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).
    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. Liu, Guangchuan & Wang, Bo & Ng, Szu Hui & Zhou, Tingting & Li, Jingyun & Deng, Nana & Zhang, Yujie & Wang, Zhaohua, 2025. "Enhancing demand response in coupled electricity and carbon markets: Optimising market signals and dispatch configurations," Energy, Elsevier, vol. 338(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. Nilsson, Anders & Bartusch, Cajsa, 2024. "Empowered or enchained? Exploring consumer perspectives on Direct Load Control," Energy Policy, Elsevier, vol. 192(C).
    2. Sridhar, Araavind & Honkapuro, Samuli & Ruiz, Fredy & Stoklasa, Jan & Annala, Salla & Wolff, Annika, 2024. "Residential consumer enrollment in demand response: An agent based approach," Applied Energy, Elsevier, vol. 374(C).
    3. Sridhar, Araavind & Honkapuro, Samuli & Ruiz, Fredy & Stoklasa, Jan & Annala, Salla & Wolff, Annika & Rautiainen, Antti, 2023. "Toward residential flexibility—Consumer willingness to enroll household loads in demand response," Applied Energy, Elsevier, vol. 342(C).
    4. Skoczkowski, Tadeusz & Bielecki, Sławomir & Wołowicz, Marcin & Sobczak, Lidia & Węglarz, Arkadiusz & Gilewski, Paweł, 2024. "Participation in demand side response. Are individual energy users interested in this?," Renewable Energy, Elsevier, vol. 232(C).
    5. 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).
    6. Wang, Aijia & Mah, Daphne Ngar-yin, 2026. "A systematic review on varieties, effectiveness and determinants of consumer engagement in the context of electricity market reforms from a European-Asian comparative perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PD).
    7. Lin, Jin & Dong, Jun & Liu, Dongran & Zhang, Yaoyu & Ma, Tongtao, 2022. "From peak shedding to low-carbon transitions: Customer psychological factors in demand response," Energy, Elsevier, vol. 238(PA).
    8. Fabianek, Paul & Liepold, Constanze & Madlener, Reinhard, 2025. "A multi-criteria assessment framework for direct load control in residential buildings from an occupants’ perspective," Energy, Elsevier, vol. 321(C).
    9. Capper, Timothy & Kuriakose, Jaise & Sharmina, Maria, 2024. "Facilitating domestic demand response in Britain’s electricity system," Utilities Policy, Elsevier, vol. 89(C).
    10. Kachirayil, Febin & Yamaguchi, Yohei & Chen, Chien-fei & McKenna, Russell, 2025. "Estimating demand response potentials of domestic appliances: Insights from a Japanese survey," Energy, Elsevier, vol. 337(C).
    11. Kim, Kyungah & Choi, Jihye & Lee, Jihee & Lee, Jongsu & Kim, Junghun, 2023. "Public preferences and increasing acceptance of time-varying electricity pricing for demand side management in South Korea," Energy Economics, Elsevier, vol. 119(C).
    12. Olga Bogdanova & Karīna Viskuba & Laila Zemīte, 2023. "A Review of Barriers and Enables in Demand Response Performance Chain," Energies, MDPI, vol. 16(18), pages 1-33, September.
    13. Ioanna-M. Chatzigeorgiou & Christos Diou & Kyriakos C. Chatzidimitriou & Georgios T. Andreou, 2021. "Demand Response Alert Service Based on Appliance Modeling," Energies, MDPI, vol. 14(10), pages 1-15, May.
    14. Wang, Bo & Deng, Nana & Li, Haoxiang & Zhao, Wenhui & Liu, Jie & Wang, Zhaohua, 2021. "Effect and mechanism of monetary incentives and moral suasion on residential peak-hour electricity usage," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    15. Nikolas Schöne & Kathrin Greilmeier & Boris Heinz, 2022. "Survey-Based Assessment of the Preferences in Residential Demand Response on the Island of Mayotte," Energies, MDPI, vol. 15(4), pages 1-30, February.
    16. Patrick Ludwig & Christian Winzer, 2022. "Tariff Menus to Avoid Rebound Peaks: Results from a Discrete Choice Experiment with Swiss Customers," Energies, MDPI, vol. 15(17), pages 1-21, August.
    17. Cruz, Carlos & Alskaif, Tarek & Palomar, Esther & Bravo, Ignacio, 2023. "Prosumers integration in aggregated demand response systems," Energy Policy, Elsevier, vol. 182(C).
    18. Sonsaard, Parinya & Ketjoy, Nipon & Mensin, Yodthong, 2023. "Market strategy options to implement Thailand demand response program policy," Energy Policy, Elsevier, vol. 173(C).
    19. Hu, Rong & Zhou, Kaile & Yin, Hui, 2024. "Reinforcement learning model for incentive-based integrated demand response considering demand-side coupling," Energy, Elsevier, vol. 308(C).
    20. Anette Boom & Sebastian Schwenen, 2021. "Is real-time pricing smart for consumers?," Journal of Regulatory Economics, Springer, vol. 60(2), pages 193-213, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:400:y:2025:i:c:s0306261925013194. 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.