From fault-detection to automated fault correction: A field study. (15th April 2022)

• Record Type: Journal Article
• Authors: Pritoni, Marco; Lin, Guanjin; Chen, Yimin; Vitti, Raphael; Weyandt, Christopher; Granderson, Jessica
• Is Part Of: Building and environment. Volume 214(2022)
• Publication Date: 2022-04-15
• Subjects: Fault correction -- Fault detection and diagnostics -- Energy efficiency -- Field testing -- Building HVAC system -- Smart building; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2022.108900
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool 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. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement. Highlights: Fault auto-correction can increase energy savings generated by FDD tools. Algorithms are tested in four buildings that use three building automation systems. Modifications of the FDD tool and the building BAS are presented. Tests are successful and do not negatively impact the system and building occupants. Technology potential and scalability challenges are drawn from the implementation.