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

Lin, Guanjing; Pritoni, Marco; Chen, Yimin; Granderson, Jessica

doi:10.3390/en13102598

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

Journal Article · Wed May 20 00:00:00 EDT 2020 · Energies (Basel)

DOI:https://doi.org/10.3390/en13102598· OSTI ID:1695725

Lin, Guanjing ^[1]; ^[1]; Chen, Yimin ^[1]; Granderson, Jessica ^[1]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

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.

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office; USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1695725

Journal Information:: Energies (Basel), Journal Name: Energies (Basel) Journal Issue: 10 Vol. 13; ISSN 1996-1073

Publisher:: MDPI AGCopyright Statement

Country of Publication:: United States

Language:: English

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