Clustering and motif identification for occupancy-centric control of an air handling unit

Hobson, Brodie W.; Gunay, H. Burak; Ashouri, Araz; Newsham, Guy R.

doi:10.1016/j.enbuild.2020.110179

Cited by 33 publications

(27 citation statements)

References 66 publications

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“…34 The installed dampers on an experimental basis display a logarithmic relationship that varies based on the difference between atmospheric pressure and the pressure in the mixing box. 35 Figure 3 shows the relationship between OAF and outdoor air damper position adapted from AMCA for three different damper authorities: 1%, 10%, and 100%. 34 Damper authority or characteristic ratio is defined as the percentage of open damper pressure drop to total system pressure drop.…”

Section: Methodsmentioning

confidence: 99%

A holistic sequential fault detection and diagnostics framework for multiple zone variable air volume air handling unit systems

Torabi

Gunay

O’Brien

et al. 2022

Building Services Engineering Research and Technology

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A holistic fault detection and diagnostics (FDD) method should explicitly consider the dependencies between faults at the system- and zone-level to isolate the root cause. A system-level fault can trigger false alarms at the zone-level, while concealing the presence of a zone-level fault. However, most FDD methods have focused on a single component/equipment without considering the importance of the interactions between zone- and system-level devices. This paper proposes a holistic hierarchical framework for FDD, combining the process of detection and diagnosis of controls hardware and sequencing logic faults affecting the actuators at the system- and zone-level. The proposed framework follows a holistic sequential procedure to diagnose faults and suppress false alarms in this order: hard faults in air handling units (AHUs), hard faults in variable air volume (VAV) zones, sequencing logic faults in AHUs, and sequencing logic faults in VAV zones. The detection of faults is performed by visualizing the discrepancies between the expected and measured operational behaviour of AHUs and VAV boxes. Examples demonstrating the framework are provided with data from 10 different VAV AHU systems. Practical application: This paper provides a sequential hierarchical FDD framework to address two main issues in VAV AHU systems: detectability and significance. Regarding detectability, the framework prioritizes hard faults over sequencing logic faults to avoid false positives and false negatives; about significance, system-level faults are prioritized over zone-level faults to triage high-impact faults in the system. The detection of faults is performed via visualizing the biases from the expected behaviour of AHU and VAV characteristics to provide an envisioning interpretation for the experts in facilities management in commercial buildings to find the root cause of the fault and fix them on-site.

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Section: Methodsmentioning

confidence: 99%

A holistic sequential fault detection and diagnostics framework for multiple zone variable air volume air handling unit systems

Torabi

Gunay

O’Brien

et al. 2022

Building Services Engineering Research and Technology

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“…While these Wi-Fi data were not available for the entire two-year period, these data could be used where available to establish baseline occupancy patterns in the buildings. This was based on a linear regression model that was trained using the number of Wi-Fi-enabled devices and ground truth occupancy data in building A from a previous study [49] . Briefly, this model discarded stagnant devices (e.g., wireless printers, computers left on overnight) and established an average of 1.2 Wi-Fi enabled devices per person in building A.…”

Section: Methodsmentioning

confidence: 99%

“…The under-occupancy of commercial office buildings relative to their design intent is a well-documented phenomenon (e.g., [48] , [49] , [50] ). When peak occupancies are below the design capacity, the minimum OA damper position can be lowered correspondingly.…”

Section: Background and Previous Workmentioning

confidence: 99%

Evaluating the impact sequences of operation have on the implementation of occupant-centric controls

Hobson

Gunay

2022

Energy and Buildings

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“…HVAC and occupancy data can be used to identify inefficiencies in outdoor airflow control and scheduling. Hobson et al [83] developed and tested a cluster analysis-based approach focusing on occupancy via Wi-Fi data; classification trees intended to project day-ahead occupancy based on day type were employed using motifs from lighting and plug-in loads.…”

Section: Rafsanjani and Ahnmentioning

confidence: 99%

“…[83] and Gunay et al[101], the occupancy function inputs Wi-Fi device count data to generate occupant count profiles of a building for weekdays and weekends separately. The function computes the earliest expected arrival time, latest expected departure time, and highest expected occupancy per floor, which are its KPIs.…”

mentioning

confidence: 99%

Development, Implementation, and Industry Reception of a Novel Multi-source, Data-driven Building Energy Management Toolkit

Markus¹

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Building energy performance is often negatively impacted by inefficient and uninformed operations, leading to wide disparities between predicted and actual energy use in commercial and institutional buildings. Though ample research in data-driven building operations and maintenance analytics has derived various methodologies for extracting energy-saving insights that can supplement operating practice, these approaches have traditionally remained disparate, limiting their application, and are exclusively prevalent in academia. Furthermore, operations personnel who regularly manage controls and maintenance of HVAC equipment can benefit from these novel approaches in augmenting their duties and optimizing building energy efficiency. This research explores the development of a novel multi-source, data-driven building energy management toolkit as a synthesis of established data-driven approaches in the literature comprising inverse energy modelling, anomaly detection and diagnostics, load disaggregation, and occupancy and occupant complaint analytics methods. The toolkit inputs various data types to detect hard and soft faults, optimize sequences of operation settings, and monitor energy flows, occupancy patterns, and occupant satisfaction. The toolkit's unique multi-source analytical approach was used to pinpoint operational deficiencies stemming from inappropriate zone temperature overheating thresholds and perimeter heating devices. Energy-saving insights were generated using data from four separate case study buildings to demonstrate the utility of the toolkit's web-based application platform. Finally, interviews with building operators and facility managers to their interpretations of insights from data-driven approaches were conducted; possible barriers were identified which inhibited industry professionals from effectively deriving and utilizing insights from the visualizations and KPIs.

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Clustering and motif identification for occupancy-centric control of an air handling unit

Cited by 33 publications

References 66 publications

A holistic sequential fault detection and diagnostics framework for multiple zone variable air volume air handling unit systems

A holistic sequential fault detection and diagnostics framework for multiple zone variable air volume air handling unit systems

Evaluating the impact sequences of operation have on the implementation of occupant-centric controls

Development, Implementation, and Industry Reception of a Novel Multi-source, Data-driven Building Energy Management Toolkit

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