Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems

Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting th...

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Main Authors: Yang, Shiyu, Wan, Man Pun, Ng, Bing Feng, Dubey, Swapnil, Henze, Gregor P., Chen, Wanyu, Baskaran, Krishnamoorthy
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/160300
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1603002022-07-19T02:25:43Z Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems Yang, Shiyu Wan, Man Pun Ng, Bing Feng Dubey, Swapnil Henze, Gregor P. Chen, Wanyu Baskaran, Krishnamoorthy School of Mechanical and Aerospace Engineering Energy Research Institute @ NTU (ERI@N) Engineering::Mechanical engineering Model Predictive Control Coordinated Control Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting the building's overall energy inefficiency and occupant comfort. A model predictive control (MPC) system that features a multi-objective MPC scheme to enable coordinated control of multiple building services for overall optimized energy efficiency, indoor thermal and visual comfort, as well as a hybrid model for predicting indoor visual comfort and lighting power is proposed. The MPC system was implemented in a test facility having two identical, side-by-side experimental cells to facilitate comparison with a building management system (BMS) employing conventional reactive feedback control. The MPC system coordinated the control of the ACMV, dynamic façade and automated dimmable lighting systems in one cell while the BMS controlled the building services in the other cell in a conventional manner. The MPC side achieved 15.1–20.7% electricity consumption reduction, as compared to the BMS side. Simultaneously, the MPC system improved indoor thermal comfort by maintaining the room within the comfortable range (−0.5 < predicted mean vote < 0.5) for 98.3% of the time, up from 91.8% of the time on the BMS side. Visual comfort, measured by indoor daylight glare probability (DGP) and horizontal illuminance level at work plane height, was maintained for the entire test period on the MPC side, improving from having visual comfort for 94.5% and 85.7% of the time, respectively, on the BMS side. Building and Construction Authority (BCA) National Research Foundation (NRF) This research is supported by the National Research Foundation (NRF) of Singapore through the Building and Construction Authority (BCA) under the Green Buildings Innovation Cluster (GBIC) grant nos. NRF2015ENC-GBICRD001-020 and GBIC-R&D/DCP02. 2022-07-19T02:25:43Z 2022-07-19T02:25:43Z 2021 Journal Article Yang, S., Wan, M. P., Ng, B. F., Dubey, S., Henze, G. P., Chen, W. & Baskaran, K. (2021). Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems. Applied Energy, 297, 117112-. https://dx.doi.org/10.1016/j.apenergy.2021.117112 0306-2619 https://hdl.handle.net/10356/160300 10.1016/j.apenergy.2021.117112 2-s2.0-85107134486 297 117112 en NRF2015ENC-GBICRD001-020 GBIC-R&D/DCP02 Applied Energy © 2021 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Model Predictive Control
Coordinated Control
spellingShingle Engineering::Mechanical engineering
Model Predictive Control
Coordinated Control
Yang, Shiyu
Wan, Man Pun
Ng, Bing Feng
Dubey, Swapnil
Henze, Gregor P.
Chen, Wanyu
Baskaran, Krishnamoorthy
Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
description Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting the building's overall energy inefficiency and occupant comfort. A model predictive control (MPC) system that features a multi-objective MPC scheme to enable coordinated control of multiple building services for overall optimized energy efficiency, indoor thermal and visual comfort, as well as a hybrid model for predicting indoor visual comfort and lighting power is proposed. The MPC system was implemented in a test facility having two identical, side-by-side experimental cells to facilitate comparison with a building management system (BMS) employing conventional reactive feedback control. The MPC system coordinated the control of the ACMV, dynamic façade and automated dimmable lighting systems in one cell while the BMS controlled the building services in the other cell in a conventional manner. The MPC side achieved 15.1–20.7% electricity consumption reduction, as compared to the BMS side. Simultaneously, the MPC system improved indoor thermal comfort by maintaining the room within the comfortable range (−0.5 < predicted mean vote < 0.5) for 98.3% of the time, up from 91.8% of the time on the BMS side. Visual comfort, measured by indoor daylight glare probability (DGP) and horizontal illuminance level at work plane height, was maintained for the entire test period on the MPC side, improving from having visual comfort for 94.5% and 85.7% of the time, respectively, on the BMS side.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Yang, Shiyu
Wan, Man Pun
Ng, Bing Feng
Dubey, Swapnil
Henze, Gregor P.
Chen, Wanyu
Baskaran, Krishnamoorthy
format Article
author Yang, Shiyu
Wan, Man Pun
Ng, Bing Feng
Dubey, Swapnil
Henze, Gregor P.
Chen, Wanyu
Baskaran, Krishnamoorthy
author_sort Yang, Shiyu
title Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
title_short Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
title_full Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
title_fullStr Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
title_full_unstemmed Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
title_sort model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems
publishDate 2022
url https://hdl.handle.net/10356/160300
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