Automated fault detection and diagnosis deployment Internet of Things solution for building energy system

Sun, Jian; Kuruganti, Teja; Fricke, Brian; Xuan, Shenglan; Li, Yanfei; Wilkerson, Wayne; Cunningham, Carlos

doi:10.1016/j.jobe.2022.105291

Automated fault detection and diagnosis deployment Internet of Things solution for building energy system

Journal Article · Tue Sep 20 00:00:00 EDT 2022 · Journal of Building Engineering

DOI:https://doi.org/10.1016/j.jobe.2022.105291· OSTI ID:1890273

Sun, Jian ^[1]; Kuruganti, Teja ^[1]; Fricke, Brian ^[1]; Xuan, Shenglan ^[2]; Li, Yanfei ^[1]; ^[3]; Cunningham, Carlos ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Johnson Control International, Norman, OK (United States)
Microsoft Corporation, Seattle, WA (United States)

The building sector is the highest energy consumer and ranks first in terms of carbon emissions among all sectors. To address these issues, decarbonization and electrification in the building energy sector are two critical missions of the new US administration. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50–52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostic (AFDD) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. Here, this study reviews existing IoT solutions developed for building energy–related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1890273

Alternate ID(s):: OSTI ID: 1890773

Journal Information:: Journal of Building Engineering, Journal Name: Journal of Building Engineering Journal Issue: 1 Vol. 61; ISSN 2352-7102

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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