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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    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. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. Lukas Sigrist & Kristof May & Andrei Morch & Peter Verboven & Pieter Vingerhoets & Luis Rouco, 2016. "On Scalability and Replicability of Smart Grid Projects—A Case Study," Energies, MDPI, vol. 9(3), pages 1-19, March.
    9. Michiel A. Heldeweg, 2017. "Normative Alignment, Institutional Resilience and Shifts in Legal Governance of the Energy Transition," Sustainability, MDPI, vol. 9(7), pages 1-34, July.
    10. Rohde, Friederike & Quitzow, Leslie, 2021. "Digitale Energiezukünfte und ihre Wirkungsmacht: Visionen der smarten Energieversorgung zwischen Technikoptimismus und Nachhaltigkeit," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 189-211.
    11. Javed, Muhammad Shahzad & Jurasz, Jakub & McPherson, Madeleine & Dai, Yanjun & Ma, Tao, 2022. "Quantitative evaluation of renewable-energy-based remote microgrids: curtailment, load shifting, and reliability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    12. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    13. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    14. Zheng Ma & Alla Asmussen & Bo Nørregaard Jørgensen, 2018. "Industrial Consumers’ Smart Grid Adoption: Influential Factors and Participation Phases," Energies, MDPI, vol. 11(1), pages 1-20, January.
    15. Ilaria Vigna & Jessica Balest & Wilmer Pasut & Roberta Pernetti, 2020. "Office Occupants’ Perspective Dealing with Energy Flexibility: A Large-Scale Survey in the Province of Bolzano," Energies, MDPI, vol. 13(17), pages 1-20, August.
    16. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    17. Barrientos, Jorge & Velilla, Esteban & Tobón Orozco, David & Villada, Fernando & López Lezama, Jesús M., 2018. "On the estimation of the price elasticity of electricity demand in the manufacturing industry of Colombia," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 88, pages 155-182, January.
    18. Kurani, Kenneth S. & TyreeHageman, Jennifer & Caperello, Nicolette, 2013. "Potential Consumer Response to Electricity Demand Response Mechanisms: Early Plug-in Electric Vehicle Drivers in San Diego, California," Institute of Transportation Studies, Working Paper Series qt1938b9bj, Institute of Transportation Studies, UC Davis.
    19. Kendel, Adnane & Lazaric, Nathalie & Maréchal, Kevin, 2017. "What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France," Energy Policy, Elsevier, vol. 108(C), pages 593-605.
    20. Aurelie Tricoire, 2015. "Uncertainty, vision, and the vitality of the emerging smart grid," Post-Print hal-02351994, HAL.

    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.