IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v199y2017icp121-141.html
   My bibliography  Save this article

Experimental assessment of room occupancy patterns in an office building. Comparison of different approaches based on CO2 concentrations and computer power consumption

Author

Listed:
  • Díaz, J.A.
  • Jiménez, M.J.

Abstract

This paper reports on various options for estimating room occupancy levels in an office building from the results of testing, and aims to find an efficient way to represent this occupancy, optimizing accuracy, cost effectiveness and the intrusiveness of measuring, which is very useful for commercial applications.

Suggested Citation

  • Díaz, J.A. & Jiménez, M.J., 2017. "Experimental assessment of room occupancy patterns in an office building. Comparison of different approaches based on CO2 concentrations and computer power consumption," Applied Energy, Elsevier, vol. 199(C), pages 121-141.
  • Handle: RePEc:eee:appene:v:199:y:2017:i:c:p:121-141
    DOI: 10.1016/j.apenergy.2017.04.082
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917304749
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2017.04.082?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. Enríquez, R. & Jiménez, M.J. & Heras, M.R., 2017. "Towards non-intrusive thermal load Monitoring of buildings: BES calibration," Applied Energy, Elsevier, vol. 191(C), pages 44-54.
    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. Yan, Lei & Tian, Wei & Han, Jiayu & Li, Zuy, 2022. "Event-driven two-stage solution to non-intrusive load monitoring," Applied Energy, Elsevier, vol. 311(C).
    2. Shen, Pengyuan & Braham, William & Yi, Yunkyu, 2018. "Development of a lightweight building simulation tool using simplified zone thermal coupling for fast parametric study," Applied Energy, Elsevier, vol. 223(C), pages 188-214.
    3. Soutullo, S. & Giancola, E. & Heras, M.R., 2018. "Dynamic energy assessment to analyze different refurbishment strategies of existing dwellings placed in Madrid," Energy, Elsevier, vol. 152(C), pages 1011-1023.
    4. Garwood, Tom Lloyd & Hughes, Ben Richard & O'Connor, Dominic & Calautit, John K. & Oates, Michael R. & Hodgson, Thomas, 2018. "A framework for producing gbXML building geometry from Point Clouds for accurate and efficient Building Energy Modelling," Applied Energy, Elsevier, vol. 224(C), pages 527-537.
    5. Liu, Yu & Liu, Wei & Shen, Yiwen & Zhao, Xin & Gao, Shan, 2021. "Toward smart energy user: Real time non-intrusive load monitoring with simultaneous switching operations," Applied Energy, Elsevier, vol. 287(C).
    6. Liu, Chao & Akintayo, Adedotun & Jiang, Zhanhong & Henze, Gregor P. & Sarkar, Soumik, 2018. "Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network," Applied Energy, Elsevier, vol. 211(C), pages 1106-1122.
    7. Wang, Shuangyuan & Li, Ran & Evans, Adrian & Li, Furong, 2020. "Regional nonintrusive load monitoring for low voltage substations and distributed energy resources," Applied Energy, Elsevier, vol. 260(C).
    8. Edwards, Richard E. & New, Joshua & Parker, Lynne E. & Cui, Borui & Dong, Jin, 2017. "Constructing large scale surrogate models from big data and artificial intelligence," Applied Energy, Elsevier, vol. 202(C), pages 685-699.

    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:199:y:2017:i:c:p:121-141. 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.