IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v25y1986i1p23-39.html
   My bibliography  Save this article

Straight-line correlations for annual energy-consumption predictions?

Author

Listed:
  • Deeble, V.C.
  • Probert, S.D.

Abstract

A method is described that enables the annual heating requirement of a building to be calculated with computational speed, yet sufficient accuracy for normal design purposes. The effects of small changes in the building's design on the annual energy requirement can be determined with this method. It combines a response-factor simulation of the building's heat-transfer performance on certain selected days, which, with a straight-line equation fitting routine, enables a prediction to be made of the thermal loads for the other days of the year.

Suggested Citation

  • Deeble, V.C. & Probert, S.D., 1986. "Straight-line correlations for annual energy-consumption predictions?," Applied Energy, Elsevier, vol. 25(1), pages 23-39.
    • Handle: RePEc:eee:appene:v:25:y:1986:i:1:p:23-39
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0306-2619(86)90060-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chaudhary, Gaurav & New, Joshua & Sanyal, Jibonananda & Im, Piljae & O’Neill, Zheng & Garg, Vishal, 2016. "Evaluation of “Autotune” calibration against manual calibration of building energy models," Applied Energy, Elsevier, vol. 182(C), pages 115-134.
    2. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    3. Leung, Philip C.M. & Lee, Eric W.M., 2013. "Estimation of electrical power consumption in subway station design by intelligent approach," Applied Energy, Elsevier, vol. 101(C), pages 634-643.
    4. Zmeureanu, Radu & Renaud, Guillaume, 2008. "Estimation of potential impact of climate change on the heating energy use of existing houses," Energy Policy, Elsevier, vol. 36(1), pages 303-310, January.
    5. Behrad Bezyan & Radu Zmeureanu, 2020. "Machine Learning for Benchmarking Models of Heating Energy Demand of Houses in Northern Canada," Energies, MDPI, vol. 13(5), pages 1-20, March.

    More about this item

    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:appene:v:25:y:1986:i:1:p:23-39. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.