Assessing barriers and research challenges for automated fault detection and diagnosis technology for small commercial buildings in the United States

Stephen Frank, Xin Jin, Daniel Studer and Amanda Farthing

Renewable and Sustainable Energy Reviews, 2018, vol. 98, issue C, 489-499

Abstract: Commercial buildings often experience faults that waste energy, decrease occupant comfort, and increase operating costs. For medium and larger commercial buildings (buildings with more than approximately 1000 m2 [approximately 10,000 ft2] of floor area), studies have shown that automated fault detection and diagnosis (AFDD) tools can help building owners and operators identify and correct faults, improving building performance and producing up to 10% energy savings. However, the existing state of the art in AFDD tools and algorithms poorly serves the needs of commercial buildings less than approximately 1000 m2 (approximately 10,000 ft2). Using the United States market and building stock as a case study, this article characterizes AFDD needs for small commercial buildings, surveys the types of AFDD tools presently available in the market, identifies gaps and barriers to widespread adoption of AFDD technology in small commercial buildings, and makes recommendations for the future research and development of small buildings AFDD technology.

Keywords: Automated fault detection and diagnosis; Small commercial buildings; Energy information systems; Market assessment (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.rser.2018.08.046

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