IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i18p6602-d1239273.html
   My bibliography  Save this article

Analysis of Residential Electricity Usage Characteristics and the Effects of Shifting Home Appliance Usage Time under a Time-of-Use Rate Plan

Author

Listed:
  • Young Mo Chung

    (Department of Electronics and Information Engineering, Hansung University, Seoul 02876, Republic of Korea)

  • Beom Jin Chung

    (Research Center for Electrical and Information Technology, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea)

  • Dong Sik Kim

    (Department of Electronics Engineering, Hankuk University of Foreign Studies, Yongin-si 17035, Republic of Korea)

Abstract

Carbon reduction programs are being introduced for carbon neutrality and energy transition to clean energy sources in various sectors, such as energy, buildings, transportation, and agriculture. In the residential electricity energy of the energy sector, the time-of-use (TOU) rate plan, which employs dynamic rates depending on energy usage times based on the advanced metering infrastructure (AMI), is being implemented for efficient electricity energy consumption. For broad expansion of the TOU rate plan, customers need information about its benefits, such as potential savings on electricity bills. In this paper, we first analyze the statistical characteristics of electricity energy usage using the metering data collected from 10 apartment complexes through AMI and develop a model to calculate the electricity bill savings. We next introduce examples of major home appliances, of which usage times can be shifted, and offer projected bill savings from the developed model. We analyze the examples from both the perspectives of households and apartment complexes. The information from this analysis is helpful in practically investigating customers’ willingness to shift the usage time for a successful implementation of the demand response program.

Suggested Citation

  • Young Mo Chung & Beom Jin Chung & Dong Sik Kim, 2023. "Analysis of Residential Electricity Usage Characteristics and the Effects of Shifting Home Appliance Usage Time under a Time-of-Use Rate Plan," Energies, MDPI, vol. 16(18), pages 1-23, September.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6602-:d:1239273
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/18/6602/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/18/6602/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    2. Verbong, Geert P.J. & Beemsterboer, Sjouke & Sengers, Frans, 2013. "Smart grids or smart users? Involving users in developing a low carbon electricity economy," Energy Policy, Elsevier, vol. 52(C), pages 117-125.
    3. Kohlhepp, Peter & Harb, Hassan & Wolisz, Henryk & Waczowicz, Simon & Müller, Dirk & Hagenmeyer, Veit, 2019. "Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 527-547.
    4. Dong Sik Kim & Wookyung Jung & Beom Jin Chung, 2021. "Analysis of the Electricity Supply Contracts for Medium-Voltage Apartments in the Republic of Korea," Energies, MDPI, vol. 14(2), pages 1-17, January.
    5. Yilmaz, S. & Weber, S. & Patel, M.K., 2019. "Who is sensitive to DSM? Understanding the determinants of the shape of electricity load curves and demand shifting: Socio-demographic characteristics, appliance use and attitudes," Energy Policy, Elsevier, vol. 133(C).
    6. Sadeghianpourhamami, N. & Demeester, T. & Benoit, D.F. & Strobbe, M. & Develder, C., 2016. "Modeling and analysis of residential flexibility: Timing of white good usage," Applied Energy, Elsevier, vol. 179(C), pages 790-805.
    Full references (including those not matched with items on IDEAS)

    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. Juan Aranda & Tasos Tsitsanis & Giannis Georgopoulos & Jose Manuel Longares, 2023. "Innovative Data-Driven Energy Services and Business Models in the Domestic Building Sector," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    2. Qiucheng Li & Jiang Hu & Bolin Yu, 2021. "Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China," Energies, MDPI, vol. 14(13), pages 1-17, June.
    3. 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).
    4. Fischbacher, Urs & Schudy, Simeon & Teyssier, Sabrina, 2021. "Heterogeneous preferences and investments in energy saving measures," Resource and Energy Economics, Elsevier, vol. 63(C).
    5. Dorothée Charlier & Mouez Fodha & Djamel Kirat, 2023. "Residential CO2 Emissions in Europe and Carbon Taxation: A Country-Level Assessment," The Energy Journal, , vol. 44(5), pages 187-206, September.
    6. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    7. Gilbert, Ben & Graff Zivin, Joshua S., 2020. "Dynamic corrective taxes with time-varying salience," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    8. Yumin Li & Yan Jiang & Shiyuan Li, 2022. "Price and income elasticities of electricity in China: Estimation and policy implications," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 76-90, November.
    9. Massimo Filippini & Luis Orea, 2014. "Applications of the stochastic frontier approach in Energy Economics," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 35-42.
    10. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2023. "The Research Agenda on Smart Grids: Foresights for Social Acceptance," Energies, MDPI, vol. 16(18), pages 1-31, September.
    11. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
    12. Choi, Kwang Hun & Kwon, Gyu Hyun, 2023. "Strategies for sensing innovation opportunities in smart grids: In the perspective of interactive relationships between science, technology, and business," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    13. Stéphane Auray & Vincenzo Caponi & Benoît Ravel, 2019. "Price Elasticity of Electricity Demand in France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 513, pages 91-103.
    14. Anthony McLean & Harriet Bulkeley & Mike Crang, 2016. "Negotiating the urban smart grid: Socio-technical experimentation in the city of Austin," Urban Studies, Urban Studies Journal Limited, vol. 53(15), pages 3246-3263, November.
    15. Esther C. van der Waal & Alexandra M. Das & Tineke van der Schoor, 2020. "Participatory Experimentation with Energy Law: Digging in a ‘Regulatory Sandbox’ for Local Energy Initiatives in the Netherlands," Energies, MDPI, vol. 13(2), pages 1-21, January.
    16. Helena Meier, Tooraj Jamasb, and Luis Orea, 2013. "Necessity or Luxury Good? Household Energy Spending and Income in Britain 1991-2007," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    17. Blázquez Gomez, Leticia M. & Filippini, Massimo & Heimsch, Fabian, 2013. "Regional impact of changes in disposable income on Spanish electricity demand: A spatial econometric analysis," Energy Economics, Elsevier, vol. 40(S1), pages 58-66.
    18. Kiran B Krishnamurthy, Chandra & Kriström, Bengt, 2013. "A cross-country analysis of residential electricity demand in 11 OECD-countries," CERE Working Papers 2013:5, CERE - the Center for Environmental and Resource Economics, revised 30 Jun 2014.
    19. Javier Bueno & Desiderio Romero-Jordán & Pablo del Río, 2020. "Analysing the Drivers of Electricity Demand in Spain after the Economic Crisis," Energies, MDPI, vol. 13(20), pages 1-18, October.
    20. Cho, Seong-Hoon & Kim, Taeyoung & Kim, Hyun Jae & Park, Kihyun & Roberts, Roland K., 2015. "Regionally-varying and regionally-uniform electricity pricing policies compared across four usage categories," Energy Economics, Elsevier, vol. 49(C), pages 182-191.

    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:16:y:2023:i:18:p:6602-:d:1239273. 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.