OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces

Passive Displacement Cooling (PDC) has gained popularity as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, w...

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Main Authors: RAVI, Anaradha, MISRA, Archan
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Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/9177
https://ink.library.smu.edu.sg/context/sis_research/article/10182/viewcontent/DCOSS_IoT___PDC_Setpoint_Control.pdf
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spelling sg-smu-ink.sis_research-101822024-08-13T05:28:45Z OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces RAVI, Anaradha MISRA, Archan Passive Displacement Cooling (PDC) has gained popularity as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, we evaluate the impact of different parameters affecting occupant comfort in a 1000m2 open-floor area (consisting of multiple zones) of a ZEB (Zero Energy Building) deployed with PDC units and tackle the problem of setting the temperature setpoint of the PDC units to assure occupant thermal comfort. We tackle two key practical challenges: (a) the zone-level (i.e., occupant-experienced) temperature differs significantly, depending on occupancy levels, from that measured by the ceiling-mounted thermal sensors that drive the PDC control loop, and (b) sparsely deployed sensors are unable to distinguish between ambient temperature variations across neighboring zones. Using extensive real-world measurement data (collected over 60 days), we devise a trace-based model that helps identify the optimum combination of PDC setpoints, collectively across multiple zones, while accommodating variations in the occupancy levels and weather conditions. We deploy OcAPO on our real-world testbed to demonstrate its efficacy: while OcAPO reliably assures occupancy comfort within a tolerance of 0.2°C, the current practice of occupancy-agnostic rule-based setpoint control violates this tolerance value 75.2% of the time. 2023-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/9177 info:doi/10.1109/DCOSS-IoT58021.2023.00030 https://ink.library.smu.edu.sg/context/sis_research/article/10182/viewcontent/DCOSS_IoT___PDC_Setpoint_Control.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University HVAC control Occupancy estimation Smart building management Thermal comfort Civil and Environmental Engineering Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic HVAC control
Occupancy estimation
Smart building management
Thermal comfort
Civil and Environmental Engineering
Software Engineering
spellingShingle HVAC control
Occupancy estimation
Smart building management
Thermal comfort
Civil and Environmental Engineering
Software Engineering
RAVI, Anaradha
MISRA, Archan
OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
description Passive Displacement Cooling (PDC) has gained popularity as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, we evaluate the impact of different parameters affecting occupant comfort in a 1000m2 open-floor area (consisting of multiple zones) of a ZEB (Zero Energy Building) deployed with PDC units and tackle the problem of setting the temperature setpoint of the PDC units to assure occupant thermal comfort. We tackle two key practical challenges: (a) the zone-level (i.e., occupant-experienced) temperature differs significantly, depending on occupancy levels, from that measured by the ceiling-mounted thermal sensors that drive the PDC control loop, and (b) sparsely deployed sensors are unable to distinguish between ambient temperature variations across neighboring zones. Using extensive real-world measurement data (collected over 60 days), we devise a trace-based model that helps identify the optimum combination of PDC setpoints, collectively across multiple zones, while accommodating variations in the occupancy levels and weather conditions. We deploy OcAPO on our real-world testbed to demonstrate its efficacy: while OcAPO reliably assures occupancy comfort within a tolerance of 0.2°C, the current practice of occupancy-agnostic rule-based setpoint control violates this tolerance value 75.2% of the time.
format text
author RAVI, Anaradha
MISRA, Archan
author_facet RAVI, Anaradha
MISRA, Archan
author_sort RAVI, Anaradha
title OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
title_short OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
title_full OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
title_fullStr OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
title_full_unstemmed OcAPO: Occupancy-aware, PDC control for open-plan, shared workspaces
title_sort ocapo: occupancy-aware, pdc control for open-plan, shared workspaces
publisher Institutional Knowledge at Singapore Management University
publishDate 2023
url https://ink.library.smu.edu.sg/sis_research/9177
https://ink.library.smu.edu.sg/context/sis_research/article/10182/viewcontent/DCOSS_IoT___PDC_Setpoint_Control.pdf
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