IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i10p2598-d360565.html
   My bibliography  Save this article

Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools

Author

Listed:
  • Guanjing Lin

    (Lawrence Berkeley National Laboratory, Berkeley, CA 94706, USA)

  • Marco Pritoni

    (Lawrence Berkeley National Laboratory, Berkeley, CA 94706, USA)

  • Yimin Chen

    (Lawrence Berkeley National Laboratory, Berkeley, CA 94706, USA)

  • Jessica Granderson

    (Lawrence Berkeley National Laboratory, Berkeley, CA 94706, USA)

Abstract

A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing.

Suggested Citation

  • Guanjing Lin & Marco Pritoni & Yimin Chen & Jessica Granderson, 2020. "Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools," Energies, MDPI, vol. 13(10), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2598-:d:360565
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/10/2598/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/10/2598/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Antonio Rosato & Marco Savino Piscitelli & Alfonso Capozzoli, 2023. "Data-Driven Fault Detection and Diagnosis: Research and Applications for HVAC Systems in Buildings," Energies, MDPI, vol. 16(2), pages 1-6, 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:gam:jeners:v:13:y:2020:i:10:p:2598-:d:360565. 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: 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.