IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v108y2013icp363-372.html
   My bibliography  Save this article

Determining appliance energy usage with a high-resolution metering system for residential natural gas meters

Author

Listed:
  • Tewolde, M.
  • Longtin, J.P.
  • Das, S.R.
  • Sharma, S.

Abstract

This paper presents a high-resolution automated meter reading system for residential gas meters, which can be used to record gas consumption for each appliance. The mechanical operation of an industry-standard residential gas meter is characterized, and the internal metering mechanism analyzed to develop a system to non-intrusively monitor gas consumption of individual appliances by resolving small amounts of gas usage at the meter. The system can be retrofitted to an existing gas meter with a module that includes a high-resolution encoder to collect gas flow data, and a microprocessor to analyze and classify appliance load profiles. This approach provides a number of attractive features including low cost, easy installation and integration with existing meter reading technologies. This system enables gas utilities to provide real-time feedback to customers on gas usage by appliance.

Suggested Citation

  • Tewolde, M. & Longtin, J.P. & Das, S.R. & Sharma, S., 2013. "Determining appliance energy usage with a high-resolution metering system for residential natural gas meters," Applied Energy, Elsevier, vol. 108(C), pages 363-372.
    • Handle: RePEc:eee:appene:v:108:y:2013:i:c:p:363-372
    DOI: 10.1016/j.apenergy.2013.03.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913002286
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.03.032?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Ueno, Tsuyoshi & Sano, Fuminori & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data," Applied Energy, Elsevier, vol. 83(2), pages 166-183, February.
    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. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    2. Chévez, Pedro Joaquín & Martini, Irene & Discoli, Carlos, 2019. "Methodology developed for the construction of an urban-energy diagnosis aimed to assess alternative scenarios: An intra-urban approach to foster cities’ sustainability," Applied Energy, Elsevier, vol. 237(C), pages 751-778.
    3. Cominola, A. & Giuliani, M. & Piga, D. & Castelletti, A. & Rizzoli, A.E., 2017. "A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring," Applied Energy, Elsevier, vol. 185(P1), pages 331-344.
    4. Ahmadi-Karvigh, Simin & Ghahramani, Ali & Becerik-Gerber, Burcin & Soibelman, Lucio, 2018. "Real-time activity recognition for energy efficiency in buildings," Applied Energy, Elsevier, vol. 211(C), pages 146-160.

    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. Penelope Buckley, 2020. "Prices, information and nudges for residential electricity conservation : A meta-analysis," Post-Print hal-02500507, HAL.
    2. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    3. Antonio Paone & Jean-Philippe Bacher, 2018. "The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art," Energies, MDPI, vol. 11(4), pages 1-19, April.
    4. Azar, Elie & Menassa, Carol C., 2014. "A comprehensive framework to quantify energy savings potential from improved operations of commercial building stocks," Energy Policy, Elsevier, vol. 67(C), pages 459-472.
    5. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    6. Murtagh, Niamh & Nati, Michele & Headley, William R. & Gatersleben, Birgitta & Gluhak, Alexander & Imran, Muhammad Ali & Uzzell, David, 2013. "Individual energy use and feedback in an office setting: A field trial," Energy Policy, Elsevier, vol. 62(C), pages 717-728.
    7. Musiliu 0. Oseni & Michael G. Poilitt & David M. Retner & Laura-Lucia Richter & Kong Chyong, 2013. "2013 EPRG Public Opinion Survey: Smart Energy Survey — Attitudes and Behaviours," Cambridge Working Papers in Economics 1352, Faculty of Economics, University of Cambridge.
    8. Chen, Victor L. & Delmas, Magali A. & Kaiser, William J. & Locke, Stephen L., 2015. "What can we learn from high-frequency appliance-level energy metering? Results from a field experiment," Energy Policy, Elsevier, vol. 77(C), pages 164-175.
    9. Xiaowei Ma & Mei Wang & Chuandong Li, 2019. "A Summary on Research of Household Energy Consumption: A Bibliometric Analysis," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    10. Stamatios Ntanos & Grigorios L. Kyriakopoulos & Garyfallos Arabatzis & Vasilios Palios & Miltiadis Chalikias, 2018. "Environmental Behavior of Secondary Education Students: A Case Study at Central Greece," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    11. Chou, Chien-Cheng & Chiang, Cheng-Ting & Wu, Pai-Yu & Chu, Chun-Ping & Lin, Chia-Ying, 2017. "Spatiotemporal analysis and visualization of power consumption data integrated with building information models for energy savings," Resources, Conservation & Recycling, Elsevier, vol. 123(C), pages 219-229.
    12. Wall, Rob & Crosbie, Tracey, 2009. "Potential for reducing electricity demand for lighting in households: An exploratory socio-technical study," Energy Policy, Elsevier, vol. 37(3), pages 1021-1031, March.
    13. Saidur, R. & Masjuki, H.H. & Jamaluddin, M.Y., 2007. "An application of energy and exergy analysis in residential sector of Malaysia," Energy Policy, Elsevier, vol. 35(2), pages 1050-1063, February.
    14. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    15. Aydinalp Koksal, Merih & Rowlands, Ian H. & Parker, Paul, 2015. "Energy, cost, and emission end-use profiles of homes: An Ontario (Canada) case study," Applied Energy, Elsevier, vol. 142(C), pages 303-316.
    16. Willis, Rachelle M. & Stewart, Rodney A. & Panuwatwanich, Kriengsak & Jones, Sarah & Kyriakides, Andreas, 2010. "Alarming visual display monitors affecting shower end use water and energy conservation in Australian residential households," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1117-1127.
    17. Sahin, Mustafa Cagri & Aydinalp Koksal, Merih, 2014. "Standby electricity consumption and saving potentials of Turkish households," Applied Energy, Elsevier, vol. 114(C), pages 531-538.
    18. Wakiyama, Takako & Kuramochi, Takeshi, 2017. "Scenario analysis of energy saving and CO2 emissions reduction potentials to ratchet up Japanese mitigation target in 2030 in the residential sector," Energy Policy, Elsevier, vol. 103(C), pages 1-15.
    19. Ian H. Rowlands & Tobi Reid & Paul Parker, 2015. "Research with disaggregated electricity end‐use data in households: review and recommendations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(5), pages 383-396, September.
    20. Handing Guo & Wanzhen Qiao & Jiren Liu, 2019. "Dynamic Feedback Analysis of Influencing Factors of Existing Building Energy-Saving Renovation Market Based on System Dynamics in China," Sustainability, MDPI, vol. 11(1), pages 1-16, January.

    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:appene:v:108:y:2013:i:c:p:363-372. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.