Results from testing of a 'cloud based' automated fault detection and diagnosis tool for AHU's

  • Ken Bruton
  • , Daniel Coakley
  • , Peter O. Donovan
  • , Marcus M. Keane
  • , D. T.J. O'Sullivan

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

4 Citations (Scopus)

Abstract

Heating Ventilation and Air Conditioning (HVAC) system energy consumption, on average, accounts for 40% of an industrial site's total energy consumption. Studies have demonstrated that continuous commissioning of building systems for optimum efficiency can yield savings of an average of over 20% of total energy cost. Automated Fault Detection and Diagnosis (AFDD) can be used to assist the commissioning process at multiple stages. This paper outlines the development of an AFDD tool for AHU's using expert rules. It outlines the results of the alpha testing phase of the tool on 18 AHU's across four commercial & industrial sites with over €104,000 annual energy savings detected by the AFDD tool.

Original languageEnglish
Title of host publicationProceedings of 2013 IEEE 18th International Conference on Emerging Technologies and Factory Automation, ETFA 2013
DOIs
Publication statusPublished - 2013
Event2013 IEEE 18th International Conference on Emerging Technologies and Factory Automation, ETFA 2013 - Cagliari, Italy
Duration: 10 Sep 201313 Sep 2013

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

Conference2013 IEEE 18th International Conference on Emerging Technologies and Factory Automation, ETFA 2013
Country/TerritoryItaly
CityCagliari
Period10/09/1313/09/13

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