Market Barriers and Drivers for the Next Generation Fault Detection and Diagnostic Tools

Commercial buildings in the U.S. consume as much as 30% excess energy compared to
buildings that operate fault free and efficiently. Fault detection and diagnostic (FDD) platforms
help to continually identify operational inefficiencies and maintain low-carbon performance.
However, the recommendations generated by FDD tools need to be implemented by technicians,
resulting in delays or lost savings opportunities. Recent research advances showed fault AUTOcorrection
integrating with commercial FDD offerings filled this gap. Seven innovative AUTOcorrection
algorithms were integrated into two FDD platforms and deployed across four
buildings. The enhanced tools successfully correct faults focusing on incorrectly programmed
schedules, override not released, control hunting, rogue zone, and suboptimal setpoints.
Although its technical efficacy has been proven in the field, fault AUTO-correction is still early
in the deployment cycle and opportunities and barriers need to be understood to reach its full
potential in market transformation.
This paper broadly introduces the new technology that automatically corrects HVAC
faults. The authors describe in detail technology potential, market barriers, and enablers for
scalability based on field testing results and interviews with the FDD providers and facility
managers. The interviewees agreed that AUTO-correction can reduce the extent to which savings
are dependent upon human intervention, scale building operators’ ability to act on FDD findings
(especially for facilities with small operation teams), and achieve significant savings. To enable
scalable deployment, future efforts are needed to overcome the barriers such as cybersecurity and
accountability concerns from building operators and standardization of control parameters used
in building automation systems.