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Effectiveness of an energy-consumption information system for residential buildings

Author

Listed:
  • Ueno, Tsuyoshi
  • Inada, Ryo
  • Saeki, Osamu
  • Tsuji, Kiichiro

Abstract

The authors have proposed a method of reducing the energy consumption in residential buildings by providing household members with information on energy consumptions in their own houses. An on-line interactive "energy-consumption information system" that displays power consumptions of, at most, 18 different appliances, power and city-gas consumption of the whole house and room temperature, for the purpose of motivating energy-saving activities has been constructed and the effectiveness of the system investigated by installing it in 10 residential buildings. The experiment showed that energy-saving consciousness was raised and energy consumption was in fact reduced by the energy-saving activities of the household members. In this paper, the system is described in detail and the effectiveness of reducing energy-consumption of the whole house and for space heating will be discussed. Also the energy-saving activities in a certain household are shown by using load duration curves.

Suggested Citation

  • Ueno, Tsuyoshi & Inada, Ryo & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system for residential buildings," Applied Energy, Elsevier, vol. 83(8), pages 868-883, August.
    • Handle: RePEc:eee:appene:v:83:y:2006:i:8:p:868-883
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    Citations

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    Cited by:

    1. Camara, N’Famory & Xu, Deyi & Binyet, Emmanuel, 2018. "Enhancing household energy consumption: How should it be done?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 669-681.
    2. Vassileva, Iana & Wallin, Fredrik & Dahlquist, Erik, 2012. "Analytical comparison between electricity consumption and behavioral characteristics of Swedish households in rented apartments," Applied Energy, Elsevier, vol. 90(1), pages 182-188.
    3. Räsänen, Teemu & Ruuskanen, Juhani & Kolehmainen, Mikko, 2008. "Reducing energy consumption by using self-organizing maps to create more personalized electricity use information," Applied Energy, Elsevier, vol. 85(9), pages 830-840, September.
    4. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2015. "The question of energy reduction: The problem(s) with feedback," Energy Policy, Elsevier, vol. 77(C), pages 89-96.
    5. Zhou, Yang & Shi, Zhixiong & Shi, Zhengyu & Gao, Qing & Wu, Libo, 2019. "Disaggregating power consumption of commercial buildings based on the finite mixture model," Applied Energy, Elsevier, vol. 243(C), pages 35-46.
    6. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    7. Diego Menegon & Daniela Lobosco & Leopoldo Micò & Joana Fernandes, 2021. "Labeling of Installed Heating Appliances in Residential Buildings: An Energy Labeling Methodology for Improving Consumers’ Awareness," Energies, MDPI, vol. 14(21), pages 1-17, October.
    8. van Dam, S.S. & Bakker, C.A. & Buiter, J.C., 2013. "Do home energy management systems make sense? Assessing their overall lifecycle impact," Energy Policy, Elsevier, vol. 63(C), pages 398-407.
    9. Shimokawa, Miyoko & Tezuka, Tetsuo, 2014. "Development of the “Home Energy Conservation Support Program” and its effects on family behavior," Applied Energy, Elsevier, vol. 114(C), pages 654-662.
    10. Hondo, Hiroki & Baba, Kenshi, 2010. "Socio-psychological impacts of the introduction of energy technologies: Change in environmental behavior of households with photovoltaic systems," Applied Energy, Elsevier, vol. 87(1), pages 229-235, January.
    11. Furszyfer Del Rio, Dylan D. & Sovacool, Benjamin K. & Bergman, Noam & Makuch, Karen E., 2020. "Critically reviewing smart home technology applications and business models in Europe," Energy Policy, Elsevier, vol. 144(C).
    12. Huebner, Gesche M. & Shipworth, David, 2017. "All about size? – The potential of downsizing in reducing energy demand," Applied Energy, Elsevier, vol. 186(P2), pages 226-233.
    13. 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).
    14. Yue, Ting & Long, Ruyin & Chen, Hong, 2013. "Factors influencing energy-saving behavior of urban households in Jiangsu Province," Energy Policy, Elsevier, vol. 62(C), pages 665-675.
    15. Ibrahim Ali Kachalla & Christian Ghiaus, 2024. "Electric Water Boiler Energy Prediction: State-of-the-Art Review of Influencing Factors, Techniques, and Future Directions," Energies, MDPI, vol. 17(2), pages 1-32, January.
    16. Tzivanidis, C. & Antonopoulos, K.A. & Gioti, F., 2011. "Numerical simulation of cooling energy consumption in connection with thermostat operation mode and comfort requirements for the Athens buildings," Applied Energy, Elsevier, vol. 88(8), pages 2871-2884, August.
    17. Fei Wang & Liming Liu & Yili Yu & Gang Li & Jessica Li & Miadreza Shafie-khah & João P. S. Catalão, 2018. "Impact Analysis of Customized Feedback Interventions on Residential Electricity Load Consumption Behavior for Demand Response," Energies, MDPI, vol. 11(4), pages 1-22, March.

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