Investigation of HVAC operation strategies for office buildings during COVID-19 pandemic

Faulkner, Cary A.; Castellini, John E.; Zuo, Wangda; Lorenzetti, David M.; Sohn, Michael D.

doi:10.1016/j.buildenv.2021.108519

Cited by 50 publications

(18 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, Feng et al [27] also refer to the fact that "cooling", "heating", and "fans" correspond to a weight EUI of 45.79%, although this is limited to Beijing, Shanghai, and Guangzhou, cities that correspond to a climate classification of "mixed", "warm", and "hot-humid" in the current research, respectively. Other authors found the same overall increasing consumption tendency, such as Ascione et al [28], Faulkner et al [37], and Zheng et al [20]. The last author concluded that prioritizing health over comfort or efficiency led to an energy consumption increase of 128% on a Chinese public building during the pandemic, which is over 100% higher than the highest value in our study (Zone 8 Tahé in Heilongjiang province).…”

Section: Discussionsupporting

confidence: 81%

“…The study aligns with our research hypothesis of energy consumption disruption under COVID-19 codes. Faulkner et al [37] ran an investigation of HVAC operation strategies for medium office buildings during the COVID-19 pandemic and concluded-resorting to Denver, Colorado climate settings-that ASHRAE's recommended MERV 13 filters reduce the virus concentration, on average, by 10% compared to MERV 10 filters; however, the use of these filters presses the energy consumption about 3%. In addition, 100% outdoor air operation reduces the virus concentration by 11% compared to MERV 10 (and 1% compared to MERV 13) but increases heating energy consumption by 54% during winter and slightly during summer.…”

Section: Operation Guidelinesmentioning

confidence: 99%

See 1 more Smart Citation

The Energy Efficiency Post-COVID-19 in China’s Office Buildings

Duarte

Cortiços

2022

Clean Technol.

View full text Add to dashboard Cite

China promptly took the leading step to mitigate the spread of COVID-19, producing the first scientific guidelines assuming health above energy consumption and significantly changing HVAC/AHU operation. The research intended to fulfill the gap by measuring the impact of the guidelines on energy use intensity, CO2 emissions, and energy operation costs related to workplaces. The guidelines are long-term sector and industry trends following occupants’ health and safety concerns, and today they are applied to nursing homes. The research extended the study to post-COVID-19 scenarios by crossing those settings with published reports on telework predictions. The methodology resorts to Building Energy Simulation software to assess the Chinese standard large office building on 8 climate zones and 17 subzones between pre- and post-COVID-19 scenarios under those guidelines. The outcomes suggest an upward trend in energy use intensity (11.70–12.46%), CO2 emissions (11.13–11.76%), and costs (9.37–9.89%) for buildings located in “warm/mixed” to “subarctic” climates, especially in colder regions with high heating demands. On the other hand, the figures for “very hot” to “hot/warm” climates lower the energy use intensity (14.76–15.47%), CO2 emissions (9%), and costs (9.64–9.77%).

show abstract

Section: Discussionsupporting

confidence: 81%

Section: Operation Guidelinesmentioning

confidence: 99%

The Energy Efficiency Post-COVID-19 in China’s Office Buildings

Duarte

Cortiços

2022

Clean Technol.

View full text Add to dashboard Cite

show abstract

“…If room-room spreading is relatively low, we investigate the impacts of single-zone mitigation strategies performed in the context of actual building operation in a multizone environment. Compared to existing SARS-CoV-2 models and tools, such as the single-zone model, FaTIMA [ 48 ], and multizone models based on Modelica [ 41 , 42 ], the proposed approach models whole-building multizone exposure risks [ 29 ]. Some recent multizone studies include risk models, such as Pease et al [ 39 ], which, however, did not solve the airflow network.…”

Section: Methodsmentioning

confidence: 99%

“…This will help identify loopholes in the renovation strategies, improve mitigation effectiveness and efficiencies, and develop building- and climate-specific, schedule-specified solutions to meet the variable, post-covid era needs. A few recent multizone simulation studies based on Modelica [ 41 , 42 ] show the importance of pressure controls and leakages in a hospital building [ 41 ] and HVAC filtrations on energy costs in an office building [ 42 ]. In addition, López-García et al linked a zonal ventilation model with a multicompartment SIS Markovian model for evaluating the infection of patients within a hospital ward [ 43 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating SARS‐CoV‐2 airborne quanta transmission and exposure risk in a mechanically ventilated multizone office building

Yan

Wang

Birnkrant

et al. 2022

Building and Environment

View full text Add to dashboard Cite

“…A large portion (between 40% and 50%) of this energy consumption can be attributed to the Heating, Ventilation, and Air Conditioning (HVAC) system [35], which is responsible for maintaining thermal comfort and indoor air quality. In addition to the dramatic energy consumption of buildings and associated greenhouse gas emissions, our ongoing experience with the COVID-19 pandemic has made it evident that our health and well-being depends to a great extent on the indoor environmental quality (IEQ) performance of the buildings that we live and work in [13]. It is therefore imperative to develop control methods to better manage their energy use and IEQ performance.…”

Section: Introductionmentioning

confidence: 99%

Diversity for transfer in learning-based control of buildings

Zhang

Afshari

et al. 2022

Proceedings of the Thirteenth ACM International Conference on Future Energy Systems

View full text Add to dashboard Cite

The application of reinforcement learning to the optimal control of building systems has gained traction in recent years as it can cut the building energy consumption and improve human comfort. Despite using sample-efficient reinforcement learning algorithms, most related work requires several months of sensor data and operational parameters of the building to train an agent that outperforms existing rule-based controllers in a large multi-zone building. Moreover, exploring the large state and action spaces can result in poor indoor environmental quality for occupants. In this paper, we propose to reduce the training cost of a policy gradient reinforcement learning algorithm by learning a library of control policies on a training building and taking advantage of both environmental and policy diversity. To transfer these policies to a target building, which can be different from the training building, we develop a simple method to assign the best pretrained policy in the library to each zone of the target building. We show that even without retraining the transferred policies on the target building, they can reduce the HVAC energy consumption by 40.4% compared to a fixed-schedule baseline and by 48.97% compared to agents trained on the target building for 5,000 months. The plausibility of our results underscores the importance of using diversity and transfer learning in multi-agent reinforcement learning settings and could pave the way for the adoption of reinforcement-learning based controllers in real buildings.

show abstract

Investigation of HVAC operation strategies for office buildings during COVID-19 pandemic

Cited by 50 publications

References 22 publications

The Energy Efficiency Post-COVID-19 in China’s Office Buildings

The Energy Efficiency Post-COVID-19 in China’s Office Buildings

Evaluating SARS‐CoV‐2 airborne quanta transmission and exposure risk in a mechanically ventilated multizone office building

Diversity for transfer in learning-based control of buildings

Contact Info

Product

Resources

About