Ventilation online monitoring and control system from the perspectives of technology application

Zhu, Huijie; Yu, Chuck Wah; Cao, Shi-Jie

doi:10.1177/1420326x19878586

Cited by 46 publications

(33 citation statements)

References 42 publications

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“…(1) The deviation errors between the prediction results of linear humidity model (LHM) and CFD results were less than 15%. Considering the well-behaved linear models (i.e., LVM's error less than 13% and LTM's error less than 20%) proposed in our previous work (Cao and Ren 2018;Ren and Cao 2019a;Zhu et al 2020), the adoption of linear models could show favorable performance in the rapid prediction of indoor environmental fields. (2) The well-behaved CRI (H) model was utilized to rapidly predict indoor humidity, and the maximum prediction error compared to CFD results was less than 15%.…”

Section: Resultsmentioning

confidence: 99%

“…(3) The design of the actual control system for temperature and humidity has not been implemented in this work. According to our previous work, the ventilation rate was adjusted corresponding to the variation of fan voltage (Zhu et al 2020;Ren and Cao 2020). Thus, we can also adjust the compressor speed (i.e., compressor input voltage) of HVAC system to obtain different inlet temperature and humidity, in order to achieve the effective regulation of integrate air conditioning system (Zhong et al 2017).…”

Section: Discussionmentioning

confidence: 99%

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Fast prediction for multi-parameters (concentration, temperature and humidity) of indoor environment towards the online control of HVAC system

2020

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Heating, ventilation and air conditioning (HVAC) systems are the most energy-consuming building implements for the improvement of indoor environmental quality (IEQ). We have developed the optimal control strategies for HVAC system to respectively achieve the optimal selections of ventilation rate and supplied air temperature with consideration of energy conservation, through the fast prediction methods by using low-dimensional linear ventilation model (LLVM) based artificial neural network (ANN) and low-dimensional linear temperature model (LLTM) based contribution ratio of indoor climate (CRI(T)). To be continued for integrated control of multi-parameters, we further developed the fast prediction model for indoor humidity by using low-dimensional linear humidity model (LLHM) and contribution ratio of indoor humidity (CRI(H)), and thermal sensation index (TS) for assessment. CFD was used to construct the prediction database for CO2, temperature and humidity. Low-dimensional linear models (LLM), including LLVM, LLTM and LLHM, were adopted to expand database for the sake of data storage reduction. Then, coupling with ANN, CRI(T) and CRI(H), the distributions of indoor CO2 concentration, temperature, and humidity were rapidly predicted on the basis of LLVM-based ANN, LLTM-based CRI(T) and LLHM-based CRI(H), respectively. Finally, according to the self-defined indices (i.e., EV, ET, EH), the optimal balancing between IEQ (indicated by CO2 concentration, PMV and TS) and energy consumption (indicated by ventilation rate, supplied air temperature and humidity) were synthetically evaluated. The total HVAC energy consumption could be reduced by 35% on the strength of current control strategies. This work can further contribute to development of the intelligent online control for HVAC systems.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Fast prediction for multi-parameters (concentration, temperature and humidity) of indoor environment towards the online control of HVAC system

2020

Self Cite

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“…53 On the basis of the ideal ‘ventilation space’, a range of ventilation technologies, such as demand-oriented ventilation, variable air volume ventilation, personalized ventilation, displacement ventilation, diffuse ceiling ventilation and optimized system sensing, monitoring and controlling technologies and data analytics can more effectively control ‘energy-saving’ and ‘healthy’ underground space environment under different scenarios. 11,15,54–57…”

Section: Discussionmentioning

confidence: 99%

Integrated design for underground space environment control of subway stations with atriums using piston ventilation

Wen

Leng

et al. 2020

Indoor and Built Environment

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In subway stations, the piston effect plays an important role in enhancing ventilation to improve subway environment and reduce energy consumption. However, it may induce negative impacts on environmental health and thermal comfort, i.e. air pollution and strong wind. Traditionally, the architecture and ventilation systems are designed separately, and normal ventilation design follows architectural layout. Actually, the architecture design can have a significant influence on the ventilation performance, e.g. airflow pattern. Therefore, this study aims to integrate the design pattern of the architecture with an appropriate ventilation system. A typical subway station of Nanjing (in China) was considered. A dynamic-mesh based computational fluid dynamics (CFD) method was adopted to simulate ventilation performance in the presence of piston effect. Field measurements were conducted to validate the numerical method. New measures were proposed from the perspectives of architectural design to improve the ventilation effect, including enlarging atrium space, adding atrium vents and funnel-shaped exits, etc. The numerical results show that the optimal architectural design could provide a significant improvement towards the airflow environment and ventilation efficiency while avoiding serious air pollution. The proposed integrated-design pattern could further facilitate the creation of an ‘energy-saving’ and ‘healthy’ underground space environment.

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“…Besides appropriate design, another issue encountered in practice is to find an online control strategy that can provide a satisfactory indoor environment with high energy performance. 45,46 For instance, Wang et al. 47 found that the total energy use of a variable air volume (VAV) air-conditioning system can be reduced by 3.3% through online optimizing outdoor air ventilation.…”

Section: Discussionmentioning

confidence: 99%

Uncertainty-based robust optimal design of cleanroom air-conditioning systems considering life-cycle performance

Zhuang

Wang

2020

Indoor and Built Environment

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Strict and simultaneous space temperature and humidity controls are often required in many applications, such as hospitals, laboratories, cleanrooms for pharmaceutical and semiconductor manufacturing. The energy intensity in such applications can be up to 100 times than typical office buildings, mainly due to the improper system design and control. Although some uncertainty-based design methods have been developed for air-conditioning systems, most of the existing systems are designed based on a certain ventilation mode while neglecting the life-cycle performance of the components. This study, therefore, proposes a robust optimal design method for cleanroom air-conditioning systems, considering the uncertainties in design parameters for inputs and operation strategies as well as the life-cycle performance of components. An adaptive full-range decoupled ventilation strategy, which incorporated five operation modes, was adopted in the design optimization. Two maintenance modes were adopted and compared to consider the flexibility of maintenance. The proposed design method has been implemented and validated in the design optimization of an existing air-conditioning system. The results showed that, compared with the conventional design, up to 54% reduction of life-cycle costs and superior satisfaction of services could be achieved by using the proposed method.

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Ventilation online monitoring and control system from the perspectives of technology application

Cited by 46 publications

References 42 publications

Fast prediction for multi-parameters (concentration, temperature and humidity) of indoor environment towards the online control of HVAC system

Fast prediction for multi-parameters (concentration, temperature and humidity) of indoor environment towards the online control of HVAC system

Integrated design for underground space environment control of subway stations with atriums using piston ventilation

Uncertainty-based robust optimal design of cleanroom air-conditioning systems considering life-cycle performance

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