Datasets of Faults in Variable Air Volume Terminal Units in a Multi-Zone Commercial Building

Jung, Sungkyun; Yoon, Yeobeom; Im, Piljae

doi:10.1038/s41597-025-05063-z

Datasets of Faults in Variable Air Volume Terminal Units in a Multi-Zone Commercial Building

Journal Article · Thu May 08 00:00:00 EDT 2025 · Scientific Data (Online)

DOI:https://doi.org/10.1038/s41597-025-05063-z· OSTI ID:2565037

Jung, Sungkyun ^[1]; ^[1]; ^[1]

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Faults in HVAC systems can decrease system efficiency and equipment lifespan, leading to 5%–30% of energy consumption being wasted in commercial buildings. We identified two common faults in HVAC variable air volume systems: a stuck damper fault in the variable air volume terminal unit and a discharge airflow sensor fault. We conducted three sets of damper stuck tests and two sets of airflow sensor tests, each including a fault-free scenario and scenarios with varying levels of faults, over one day. The faults were implemented in Oak Ridge National Laboratory’s two-story Flexible Research Platform building to generate a high-quality, well-controlled dataset covering fault-induced and fault-free scenarios. The test building, fault test scenarios, and data validation are described here. The open-source dataset includes 1 min intervals of weather and building data on the presence and absence of building faults. This dataset can be used to analyze the effects of HVAC system faults on system operation and indoor building conditions, and to develop or evaluate a fault detection and diagnosis algorithm.

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

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office; USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2565037

Alternate ID(s):: OSTI ID: 2573366

Journal Information:: Scientific Data (Online), Journal Name: Scientific Data (Online) Journal Issue: 1 Vol. 12; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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