An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system
For addressing the energy waste resulted by over-ventilation or under-ventilation in conventional demand-controlled ventilation system, an air balancing strategy is proposed to solve the over-ventilation and under-ventilation problems of the multi-zone demand-controlled ventilation system. In this s...
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sg-ntu-dr.10356-1511452021-06-29T01:20:06Z An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system Jing, Gang Cai, Wenjian Zhang, Xin Cui, Can Yin, Xiaohong Xian, Huacai School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Ventilation Air Balancing For addressing the energy waste resulted by over-ventilation or under-ventilation in conventional demand-controlled ventilation system, an air balancing strategy is proposed to solve the over-ventilation and under-ventilation problems of the multi-zone demand-controlled ventilation system. In this study, an energy-saving oriented mathematical model is constructed to simulate the non-linear behavior of the multi-zone ventilation system and Bayesian linear regression supervised machine learning algorithm is used to estimate the unknown parameters of the constructed model. On the basis of the developed model, the damper control method is established to determine the position of the damper according to the desired airflow rate to ensure the system well-balanced. Therefore, with the constructed system model and the damper control method, the system can be well-balanced to overcome the disadvantages of over-ventilation and under-ventilation, and consumes less energy compared to the system that are not balanced. The performance of the proposed air balancing strategy for demand-controlled ventilation system is practically tested in an experimental rig with five terminals and validated by comparing to the demand-controlled ventilation strategy without air balancing. The experimental results demonstrate that the proposed strategy achieved the desired airflow rate within 4.6% maximum absolute percentage error, and also achieved a maximum value 14.3% for fan power reduction compared to conventional the strategy without air balancing. National Research Foundation (NRF) This work was partially funded by National Research Foundation of Singapore under the grant NRF2014EWT-EIRP003-014, NRF2013EWT-EIRP004-019, NRF2011 NRF-CRP001-090, the scholarship from China Scholarship Council (No. 201704000002) and the Science and technology plan project of Shandong higher education institutions (No. J16LN26, No. J17KA210). 2021-06-29T01:20:06Z 2021-06-29T01:20:06Z 2019 Journal Article Jing, G., Cai, W., Zhang, X., Cui, C., Yin, X. & Xian, H. (2019). An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system. Energy, 172, 1053-1065. https://dx.doi.org/10.1016/j.energy.2019.02.044 0360-5442 https://hdl.handle.net/10356/151145 10.1016/j.energy.2019.02.044 2-s2.0-85061634495 172 1053 1065 en NRF2014EWT-EIRP003-014 NRF2013EWT-EIRP004-019 NRF2011 NRF-CRP001-090 Energy © 2019 Elsevier Ltd. All rights reserved. |
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Engineering::Electrical and electronic engineering Ventilation Air Balancing Jing, Gang Cai, Wenjian Zhang, Xin Cui, Can Yin, Xiaohong Xian, Huacai An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
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For addressing the energy waste resulted by over-ventilation or under-ventilation in conventional demand-controlled ventilation system, an air balancing strategy is proposed to solve the over-ventilation and under-ventilation problems of the multi-zone demand-controlled ventilation system. In this study, an energy-saving oriented mathematical model is constructed to simulate the non-linear behavior of the multi-zone ventilation system and Bayesian linear regression supervised machine learning algorithm is used to estimate the unknown parameters of the constructed model. On the basis of the developed model, the damper control method is established to determine the position of the damper according to the desired airflow rate to ensure the system well-balanced. Therefore, with the constructed system model and the damper control method, the system can be well-balanced to overcome the disadvantages of over-ventilation and under-ventilation, and consumes less energy compared to the system that are not balanced. The performance of the proposed air balancing strategy for demand-controlled ventilation system is practically tested in an experimental rig with five terminals and validated by comparing to the demand-controlled ventilation strategy without air balancing. The experimental results demonstrate that the proposed strategy achieved the desired airflow rate within 4.6% maximum absolute percentage error, and also achieved a maximum value 14.3% for fan power reduction compared to conventional the strategy without air balancing. |
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School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Jing, Gang Cai, Wenjian Zhang, Xin Cui, Can Yin, Xiaohong Xian, Huacai |
format |
Article |
author |
Jing, Gang Cai, Wenjian Zhang, Xin Cui, Can Yin, Xiaohong Xian, Huacai |
author_sort |
Jing, Gang |
title |
An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
title_short |
An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
title_full |
An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
title_fullStr |
An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
title_full_unstemmed |
An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
title_sort |
energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/151145 |
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1703971243842076672 |