Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system
Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separa...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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2022
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| Online Access: | https://hdl.handle.net/10356/155379 |
| _version_ | 1826132484463525888 |
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| author | Yang, Shiyu Wan, Man Pun Ng, Bing Feng Dubey, Swapnil Henze, Gregor P. Chen, Wanyu Baskaran, Krishnamoorthy |
| 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 |
| author_sort | Yang, Shiyu |
| collection | NTU |
| description | Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separate sensible and latent cooling (SSLC) systems. However, a sophisticated control technique is needed to coordinate the control of multiple cooling coils in such systems. This paper presents a novel model predictive control (MPC) developed for a DOAS-assisted SSLC system. The MPC adopts a linear state-space model that captures building thermodynamics, thermal comfort and ACMV for building response prediction and optimization. Subsequently, a multi-objective cost function is employed to optimize energy use and thermal comfort while fulfilling constraints of predicted mean vote (PMV) (-0.5, 0.5) and relative humidity (0%, 65%) in buildings. The performance of the MPC for controlling a conventional single-coil air-handling unit (AHU) system and a DOAS-assisted SSLC system is experimentally investigated and compared to a conventional feedback-control-based building management system (BMS). The MPC system achieved 18% and 20% electricity savings for the single-coil AHU and DOAS-assisted SSLC, respectively, as compared to the BMS controlled single-coil AHU. Furthermore, indoor thermal comfort is significantly improved, compared to the BMS. DOAS-assisted SSLC is shown to be advantageous compared to single-coil AHU to achieve better indoor environment in terms of thermal comfort and humidity, when both systems are controlled by MPC. |
| first_indexed | 2025-02-19T03:35:22Z |
| format | Journal Article |
| id | ntu-10356/155379 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:35:22Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1553792022-02-19T20:11:22Z Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system 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 Separate Sensible and Latent Cooling Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separate sensible and latent cooling (SSLC) systems. However, a sophisticated control technique is needed to coordinate the control of multiple cooling coils in such systems. This paper presents a novel model predictive control (MPC) developed for a DOAS-assisted SSLC system. The MPC adopts a linear state-space model that captures building thermodynamics, thermal comfort and ACMV for building response prediction and optimization. Subsequently, a multi-objective cost function is employed to optimize energy use and thermal comfort while fulfilling constraints of predicted mean vote (PMV) (-0.5, 0.5) and relative humidity (0%, 65%) in buildings. The performance of the MPC for controlling a conventional single-coil air-handling unit (AHU) system and a DOAS-assisted SSLC system is experimentally investigated and compared to a conventional feedback-control-based building management system (BMS). The MPC system achieved 18% and 20% electricity savings for the single-coil AHU and DOAS-assisted SSLC, respectively, as compared to the BMS controlled single-coil AHU. Furthermore, indoor thermal comfort is significantly improved, compared to the BMS. DOAS-assisted SSLC is shown to be advantageous compared to single-coil AHU to achieve better indoor environment in terms of thermal comfort and humidity, when both systems are controlled by MPC. Building and Construction Authority (BCA) National Research Foundation (NRF) Accepted version 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 no. NRF2015ENC-GBICRD001-020. T 2022-02-18T06:38:36Z 2022-02-18T06:38:36Z 2020 Journal Article Yang, S., Wan, M. P., Ng, B. F., Dubey, S., Henze, G. P., Chen, W. & Baskaran, K. (2020). Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system. Applied Energy, 257, 113920-. https://dx.doi.org/10.1016/j.apenergy.2019.113920 0306-2619 https://hdl.handle.net/10356/155379 10.1016/j.apenergy.2019.113920 2-s2.0-85074174562 257 113920 en NRF2015ENC-GBICRD001-020 Applied Energy © 2019 Elsevier Ltd. All rights reserved. This paper was published in Applied Energy and is made available with permission of Elsevier Ltd. application/pdf |
| spellingShingle | Engineering::Mechanical engineering Model Predictive Control Separate Sensible and Latent Cooling Yang, Shiyu Wan, Man Pun Ng, Bing Feng Dubey, Swapnil Henze, Gregor P. Chen, Wanyu Baskaran, Krishnamoorthy Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title | Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title_full | Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title_fullStr | Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title_full_unstemmed | Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title_short | Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system |
| title_sort | experimental study of model predictive control for an air conditioning system with dedicated outdoor air system |
| topic | Engineering::Mechanical engineering Model Predictive Control Separate Sensible and Latent Cooling |
| url | https://hdl.handle.net/10356/155379 |
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