IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt6qd1x5js.html
   My bibliography  Save this paper

Characterization and Potential of Home Energy Management (HEM) Technology

Author

Listed:
  • Karlin, Beth
  • Ford, Rebecca
  • Sanguinetti, Angela
  • Squiers, Cassandra
  • Gannon, John
  • Rajukumar, Mukund
  • Donnelly, Kat A.

Abstract

The Home Energy Management (HEM) market is rapidly expanding alongside substantial investments to improve energy efficiency and upgrade electricity infrastructure to a smart grid. These changes enable consumers to take greater control of their energy use, which can be enabled through the use of Home Energy Management Systems (HEMS). HEMS can be broadly defined as those systems (including both hardware and software linked together via a network) that enable households to manage their energy consumption. This can be done in one (or both) of two ways: HEMS can provide energy consumers with information about how they use energy in the home and/or prompts to modify consumption. HEMS can provide the household (or third parties) the ability to control energy- consuming processes in the home, either remotely via a smart phone or web service or based on a set of rules, which can be scheduled or optimized based on user behavior. As such, HEMS enable the delivery of a wide range of both household and utility objectives around energy management, financial benefits, comfort and convenience, greenhouse gas emissions reductions, as well as to ensure access to a reliable energy supply. The HEMS sector is growing rapidly, and at the time of writing this report, 12 distinct product types or categories that make up a home energy management system were identified. These fall into three groups: (1) user interfaces, (2) smart hardware, and (3) software platforms. The rapid expansion of the HEM market and the desire for increasing levels of interoperability between products and platforms has led to the emergence of new types of communication protocols and alliances based on these. Over the coming years, this may open up the opportunity for further engagement between manufacturer and a variety of developers to create fully integrated home management solutions that better meet the needs of customers.

Suggested Citation

  • Karlin, Beth & Ford, Rebecca & Sanguinetti, Angela & Squiers, Cassandra & Gannon, John & Rajukumar, Mukund & Donnelly, Kat A., 2015. "Characterization and Potential of Home Energy Management (HEM) Technology," Institute of Transportation Studies, Working Paper Series qt6qd1x5js, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt6qd1x5js
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/6qd1x5js.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Isamu Matsukawa, 2004. "The Effects of Information on Residential Demand for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-18.
    2. Hargreaves, Tom & Nye, Michael & Burgess, Jacquelin, 2010. "Making energy visible: A qualitative field study of how householders interact with feedback from smart energy monitors," Energy Policy, Elsevier, vol. 38(10), pages 6111-6119, October.
    3. Broman Toft, Madeleine & Schuitema, Geertje & Thøgersen, John, 2014. "Responsible technology acceptance: Model development and application to consumer acceptance of Smart Grid technology," Applied Energy, Elsevier, vol. 134(C), pages 392-400.
    4. Karlin, Beth & Sanguinetti, Angela & Davis, Nora & Bendanna, Kristen & Holdsworth, Kristen & Baker, Jessie & Kirkby, David & Stokols, Daniel, 2015. "Diffusion of Feedback: Perceptions and Adoption of Devices in the Residential Market," Institute of Transportation Studies, Working Paper Series qt0cv5g621, Institute of Transportation Studies, UC Davis.
    5. Hutton, R Bruce, et al, 1986. "Effects of Cost-Related Feedback on Consumer Knowledge and Consumption Behavior: A Field Experimental Approach," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(3), pages 327-336, December.
    6. Midden, Cees J. H. & Meter, Joanne F. & Weenig, Mieneke H. & Zieverink, Henk J. A., 1983. "Using feedback, reinforcement and information to reduce energy consumption in households: A field-experiment," Journal of Economic Psychology, Elsevier, vol. 3(1), pages 65-86.
    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. Li-Hsing Shih & Yi-Cin Jheng, 2017. "Selecting Persuasive Strategies and Game Design Elements for Encouraging Energy Saving Behavior," Sustainability, MDPI, vol. 9(7), pages 1-18, July.
    2. WeiYu Ji & Edwin H. W. Chan, 2019. "Critical Factors Influencing the Adoption of Smart Home Energy Technology in China: A Guangdong Province Case Study," Energies, MDPI, vol. 12(21), pages 1-24, November.
    3. Fleiß, Eva & Hatzl, Stefanie & Rauscher, Jürgen, 2024. "Smart energy technology: A survey of adoption by individuals and the enabling potential of the technologies," Technology in Society, Elsevier, vol. 76(C).
    4. Tuomela, Sanna & de Castro Tomé, Mauricio & Iivari, Netta & Svento, Rauli, 2021. "Impacts of home energy management systems on electricity consumption," Applied Energy, Elsevier, vol. 299(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. Paolo Zangheri & Tiago Serrenho & Paolo Bertoldi, 2019. "Energy Savings from Feedback Systems: A Meta-Studies’ Review," Energies, MDPI, vol. 12(19), pages 1-18, October.
    2. Grégoire Wallenborn & Catherine Rousseau & Karine Thollier, 2006. "Détermination de profils de ménages pour une utilisation plus rationnelle de l’energie," ULB Institutional Repository 2013/192217, ULB -- Universite Libre de Bruxelles.
    3. Julien Lancelot Michellod & Declan Kuch & Christian Winzer & Martin K. Patel & Selin Yilmaz, 2022. "Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector," Energies, MDPI, vol. 15(20), pages 1-25, October.
    4. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
    5. Kua, H.W. & Wong, S.E., 2012. "Lessons for integrated household energy conservation policies from an intervention study in Singapore," Energy Policy, Elsevier, vol. 47(C), pages 49-56.
    6. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    7. Rieger, Alexander & Thummert, Robert & Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang, 2016. "Estimating the benefits of cooperation in a residential microgrid: A data-driven approach," Applied Energy, Elsevier, vol. 180(C), pages 130-141.
    8. Oltra, Christian & Boso, Alex & Espluga, Josep & Prades, Ana, 2013. "A qualitative study of users' engagement with real-time feedback from in-house energy consumption displays," Energy Policy, Elsevier, vol. 61(C), pages 788-792.
    9. Mizobuchi, Kenichi & Takeuchi, Kenji, 2013. "The influences of financial and non-financial factors on energy-saving behaviour: A field experiment in Japan," Energy Policy, Elsevier, vol. 63(C), pages 775-787.
    10. Kazutoshi Tsuda & Michinori Uwasu & Keishiro Hara & Yukari Fuchigami, 2017. "Approaches to induce behavioral changes with respect to electricity consumption," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 7(1), pages 30-38, March.
    11. 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.
    12. Lillemo, Shuling Chen, 2014. "Measuring the effect of procrastination and environmental awareness on households' energy-saving behaviours: An empirical approach," Energy Policy, Elsevier, vol. 66(C), pages 249-256.
    13. Burchell, Kevin & Rettie, Ruth & Roberts, Tom C., 2016. "Householder engagement with energy consumption feedback: the role of community action and communications," Energy Policy, Elsevier, vol. 88(C), pages 178-186.
    14. Morgane Innocent & Agnès François-Lecompte & Nolwenn Roudaut, 2020. "Comparison of human versus technological support to reduce domestic electricity consumption in France," Post-Print hal-02450849, HAL.
    15. Brown, Christopher J. & Markusson, Nils, 2019. "The responses of older adults to smart energy monitors," Energy Policy, Elsevier, vol. 130(C), pages 218-226.
    16. Gilbert E. Metcalf, 2006. "Energy Conservation in the United States: Understanding its Role in Climate Policy," NBER Working Papers 12272, National Bureau of Economic Research, Inc.
    17. Liu, Xingjian & Wang, Mingshu & Qiang, Wei & Wu, Kang & Wang, Xiaomi, 2020. "Urban form, shrinking cities, and residential carbon emissions: Evidence from Chinese city-regions," Applied Energy, Elsevier, vol. 261(C).
    18. Foxon, Timothy J., 2013. "Transition pathways for a UK low carbon electricity future," Energy Policy, Elsevier, vol. 52(C), pages 10-24.
    19. Qianchun Dai & Kequn Cheng, 2022. "What Drives the Adoption of Agricultural Green Production Technologies? An Extension of TAM in Agriculture," Sustainability, MDPI, vol. 14(21), pages 1-18, November.
    20. Yuting Zhang & Xiaofen Yu & Ning Cai & Yong Li, 2020. "Analyzing the Employees’ New Media Use in the Energy Industry：The Role of Creative Self-Efficacy, Perceived Usefulness and Leaders’ Use," Sustainability, MDPI, vol. 12(3), pages 1-13, January.

    More about this item

    Keywords

    Engineering;

    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:cdl:itsdav:qt6qd1x5js. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.