IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v114y2016icp478-491.html

Estimating the hourly electricity profile of Japanese households – Coupling of engineering and statistical methods

Author

Listed:
  • Shiraki, Hiroto
  • Nakamura, Shogo
  • Ashina, Shuichi
  • Honjo, Keita

Abstract

Understanding the hourly electricity profile and the electricity consumption by each appliance is essential for encouraging energy-saving measures in the household sector. There are two methods for identifying energy consumption for households in existing studies: the engineering and the statistical methods. Both methods have strengths and limitations. In this study, we developed a hybrid method based on the statistical method by combining following three steps using knowledge of the engineering method; externalizing the electricity consumption for the refrigerator, adding the number of at-home-and-awake members as explanatory variables, and restricting appliance usage hours. The proposed hybrid method could adequately reproduce the total hourly electricity consumption and seasonal variation compared to the engineering method, and could decompose major appliances, some of which that were not disaggregated by the statistical method. For the quantitative analysis of the model improvement, we calculated Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for each method with direct metering data. For most of appliances, RMSE and MAE of hybrid model were improved from 11% to 71% compared to the existing methods. The collection of more samples to increase the accuracy of the estimation and application to areas of low statistical data availability are future steps.

Suggested Citation

  • Shiraki, Hiroto & Nakamura, Shogo & Ashina, Shuichi & Honjo, Keita, 2016. "Estimating the hourly electricity profile of Japanese households – Coupling of engineering and statistical methods," Energy, Elsevier, vol. 114(C), pages 478-491.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:478-491
    DOI: 10.1016/j.energy.2016.08.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216311227
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.08.019?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. Michael Parti & Cynthia Parti, 1980. "The Total and Appliance-Specific Conditional Demand for Electricity in the Household Sector," Bell Journal of Economics, The RAND Corporation, vol. 11(1), pages 309-321, Spring.
    2. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    3. Shimoda, Yoshiyuki & Asahi, Takahiro & Taniguchi, Ayako & Mizuno, Minoru, 2007. "Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model," Energy, Elsevier, vol. 32(9), pages 1617-1633.
    4. Larsen, Bodil Merethe & Nesbakken, Runa, 2004. "Household electricity end-use consumption: results from econometric and engineering models," Energy Economics, Elsevier, vol. 26(2), pages 179-200, March.
    5. repec:aen:journl:1984v05-03-a06 is not listed on IDEAS
    6. Newsham, Guy R. & Donnelly, Cara L., 2013. "A model of residential energy end-use in Canada: Using conditional demand analysis to suggest policy options for community energy planners," Energy Policy, Elsevier, vol. 59(C), pages 133-142.
    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. Yujiro Hirano & Tomohiko Ihara & Masayuki Hara & Keita Honjo, 2020. "Estimation of Direct and Indirect Household CO 2 Emissions in 49 Japanese Cities with Consideration of Regional Conditions," Sustainability, MDPI, vol. 12(11), pages 1-17, June.
    2. Oka, Kazutaka & Mizutani, Wataru & Ashina, Shuichi, 2020. "Climate change impacts on potential solar energy production: A study case in Fukushima, Japan," Renewable Energy, Elsevier, vol. 153(C), pages 249-260.
    3. Akito Ozawa & Ryota Furusato & Yoshikuni Yoshida, 2017. "Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan," Sustainability, MDPI, vol. 9(4), pages 1-23, March.
    4. Francesco Mancini & Gianluigi Lo Basso & Livio De Santoli, 2019. "Energy Use in Residential Buildings: Characterisation for Identifying Flexible Loads by Means of a Questionnaire Survey," Energies, MDPI, vol. 12(11), pages 1-19, May.
    5. Anatolyy Dzyuba & Irina Solovyeva, 2020. "Demand-side Management in Territorial Entities based on their Volatility Trends," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 302-315.
    6. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    7. Liu, Yixing & Liu, Bo & Guo, Xiaoyu & Xu, Yiqiao & Ding, Zhengtao, 2023. "Household profile identification for retailers based on personalized federated learning," Energy, Elsevier, vol. 275(C).
    8. Leithon, Johann & Werner, Stefan & Koivunen, Visa, 2020. "Cost-aware renewable energy management: Centralized vs. distributed generation," Renewable Energy, Elsevier, vol. 147(P1), pages 1164-1179.
    9. Keita Honjo & Hiroto Shiraki & Shuichi Ashina, 2018. "Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    10. Anatolyy Dzyuba & Irina Solovyeva, 2020. "Price-based Demand-side Management Model for Industrial and Large Electricity Consumers," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 135-149.
    11. Laib, I. & Hamidat, A. & Haddadi, M. & Ramzan, N. & Olabi, A.G., 2018. "Study and simulation of the energy performances of a grid-connected PV system supplying a residential house in north of Algeria," Energy, Elsevier, vol. 152(C), pages 445-454.
    12. Nadimi, Reza & Goto, Mika, 2026. "Analyzing incentivized self-consumption and integration of rooftop solar and battery electric vehicles in residential energy systems," Renewable Energy, Elsevier, vol. 258(C).
    13. Inoue, Nozomu & Matsumoto, Shigeru, 2019. "An examination of losses in energy savings after the Japanese Top Runner Program?," Energy Policy, Elsevier, vol. 124(C), pages 312-319.

    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. Papineau, Maya & Yassin, Kareman & Newsham, Guy & Brice, Sarah, 2021. "Conditional demand analysis as a tool to evaluate energy policy options on the path to grid decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Shigeru Matsumoto, 2015. "Electric Appliance Ownership and Usage: Application of Conditional Demand Analysis to Japanese Household Data," Proceedings of International Academic Conferences 3105452, International Institute of Social and Economic Sciences.
    3. Matsumoto, Shigeru, 2016. "How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data," Energy Policy, Elsevier, vol. 94(C), pages 214-223.
    4. Soo-Jin Lee & You-Jeong Kim & Hye-Sun Jin & Sung-Im Kim & Soo-Yeon Ha & Seung-Yeong Song, 2019. "Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis," Energies, MDPI, vol. 12(12), pages 1-18, June.
    5. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    6. Jia, Jun-Jun & Ni, Jinlan & Wei, Chu, 2023. "Residential responses to service-specific electricity demand: Case of China," China Economic Review, Elsevier, vol. 78(C).
    7. Cao, Jing & Ho, Mun Sing & Li, Yating & Newell, Richard G. & Pizer, William A., 2019. "Chinese residential electricity consumption: Estimation and forecast using micro-data," Resource and Energy Economics, Elsevier, vol. 56(C), pages 6-27.
    8. Anna Risch & Claire Salmon, 2017. "What matters in residential energy consumption: evidence from France," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 40(1/2), pages 79-116.
    9. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
    10. Dongjun Suh & Seongju Chang, 2012. "An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea," Energies, MDPI, vol. 5(11), pages 1-20, November.
    11. repec:aen:journl:ej36-4-larsen is not listed on IDEAS
    12. repec:aen:journl:ej37-4-vesterberg is not listed on IDEAS
    13. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    14. Estiri, Hossein & Zagheni, Emilio, 2018. "Evaluating the Age-Energy Consumption Profile in Residential Buildings," SocArXiv yqkva, Center for Open Science.
    15. Grandjean, A. & Adnot, J. & Binet, G., 2012. "A review and an analysis of the residential electric load curve models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6539-6565.
    16. Ye, Zhongnan & Cheng, Kuangly & Hsu, Shu-Chien & Wei, Hsi-Hsien & Cheung, Clara Man, 2021. "Identifying critical building-oriented features in city-block-level building energy consumption: A data-driven machine learning approach," Applied Energy, Elsevier, vol. 301(C).
    17. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    18. Yildiz, B. & Bilbao, J.I. & Dore, J. & Sproul, A.B., 2017. "Recent advances in the analysis of residential electricity consumption and applications of smart meter data," Applied Energy, Elsevier, vol. 208(C), pages 402-427.
    19. Hannah Goozee, 2017. "Energy, poverty and development: a primer for the Sustainable Development Goals," Working Papers 156, International Policy Centre.
    20. Mattias Vesterberg & Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, , vol. 37(4), pages 141-164, October.
    21. 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.
    22. Hamed Nabizadeh Rafsanjani & Changbum R. Ahn & Mahmoud Alahmad, 2015. "A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings," Energies, MDPI, vol. 8(10), pages 1-34, October.

    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:energy:v:114:y:2016:i:c:p:478-491. 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.journals.elsevier.com/energy .

    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.