A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings

Xuezheng Wang; Bing Dong; Jianshun Zhang; Bhavesh Gupta; Moises Ramirez; Zhenlei Liu

doi:10.1007/978-981-19-9822-5_233

A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings

Xuezheng Wang, Bing Dong, Jianshun Zhang, Bhavesh Gupta, Moises Ramirez, Zhenlei Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Before the COVID-19 pandemic, buildings accounted for more than 40% of the total energy. The need for improving indoor air quality (IAQ) not only during the pandemic but also in the post-pandemic era presents a unique opportunity for innovation that meets the needs in both environmental health and building energy efficiency. Carbon-dioxide concentration has been widely used for modeling and quantifying IAQ. Model predictive control (MPC) has been demonstrated promising potential in improving the energy performance of building heat ventilating and air conditioning (HVAC) systems. However, little research fell on both IAQ and energy efficiency improvement. In the paper, we developed a data-driven, coupled—IAQ and energy simulation method that combines thermal comfort and indoor air quality, specifically CO₂. A new MPC algorithm was developed correspondingly to improve both energy-saving and indoor health. The results of a one-week, national-wide cooling season simulation indicate at most 50% energy savings while maintaining less than 700 PPM indoor CO₂.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Building Energy and Environment
Editors	Liangzhu Leon Wang, Hua Ge, Mohamed Ouf, Zhiqiang John Zhai, Dahai Qi, Chanjuan Sun, Dengjia Wang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	2183-2192
Number of pages	10
ISBN (Print)	9789811998218
DOIs	https://doi.org/10.1007/978-981-19-9822-5_233
State	Published - 2023
Externally published	Yes
Event	5th International Conference on Building Energy and Environment, COBEE 2022 - Montreal, Canada Duration: Jul 25 2022 → Jul 29 2022

Publication series

Name	Environmental Science and Engineering
ISSN (Print)	1863-5520
ISSN (Electronic)	1863-5539

Conference

Conference	5th International Conference on Building Energy and Environment, COBEE 2022
Country/Territory	Canada
City	Montreal
Period	07/25/22 → 07/29/22

Funding

Acknowledgements This research was jointly sponsored by Honeywell International Inc. and Syracuse University.

Keywords

Building modeling
Energy efficiency
Indoor air quality
Model predictive control

Access to Document

10.1007/978-981-19-9822-5_233

Cite this

Wang, X., Dong, B., Zhang, J., Gupta, B., Ramirez, M., & Liu, Z. (2023). A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings. In L. L. Wang, H. Ge, M. Ouf, Z. J. Zhai, D. Qi, C. Sun, & D. Wang (Eds.), Proceedings of the 5th International Conference on Building Energy and Environment (pp. 2183-2192). (Environmental Science and Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-9822-5_233

Wang, Xuezheng ; Dong, Bing ; Zhang, Jianshun et al. / A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings. Proceedings of the 5th International Conference on Building Energy and Environment. editor / Liangzhu Leon Wang ; Hua Ge ; Mohamed Ouf ; Zhiqiang John Zhai ; Dahai Qi ; Chanjuan Sun ; Dengjia Wang. Springer Science and Business Media Deutschland GmbH, 2023. pp. 2183-2192 (Environmental Science and Engineering).

@inproceedings{fc7bb1450287455baf9cb54aa84ee37d,

title = "A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings",

abstract = "Before the COVID-19 pandemic, buildings accounted for more than 40% of the total energy. The need for improving indoor air quality (IAQ) not only during the pandemic but also in the post-pandemic era presents a unique opportunity for innovation that meets the needs in both environmental health and building energy efficiency. Carbon-dioxide concentration has been widely used for modeling and quantifying IAQ. Model predictive control (MPC) has been demonstrated promising potential in improving the energy performance of building heat ventilating and air conditioning (HVAC) systems. However, little research fell on both IAQ and energy efficiency improvement. In the paper, we developed a data-driven, coupled—IAQ and energy simulation method that combines thermal comfort and indoor air quality, specifically CO2. A new MPC algorithm was developed correspondingly to improve both energy-saving and indoor health. The results of a one-week, national-wide cooling season simulation indicate at most 50% energy savings while maintaining less than 700 PPM indoor CO2.",

keywords = "Building modeling, Energy efficiency, Indoor air quality, Model predictive control",

author = "Xuezheng Wang and Bing Dong and Jianshun Zhang and Bhavesh Gupta and Moises Ramirez and Zhenlei Liu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 5th International Conference on Building Energy and Environment, COBEE 2022 ; Conference date: 25-07-2022 Through 29-07-2022",

year = "2023",

doi = "10.1007/978-981-19-9822-5_233",

language = "English",

isbn = "9789811998218",

series = "Environmental Science and Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

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editor = "Wang, {Liangzhu Leon} and Hua Ge and Mohamed Ouf and Zhai, {Zhiqiang John} and Dahai Qi and Chanjuan Sun and Dengjia Wang",

booktitle = "Proceedings of the 5th International Conference on Building Energy and Environment",

}

Wang, X, Dong, B, Zhang, J, Gupta, B, Ramirez, M & Liu, Z 2023, A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings. in LL Wang, H Ge, M Ouf, ZJ Zhai, D Qi, C Sun & D Wang (eds), Proceedings of the 5th International Conference on Building Energy and Environment. Environmental Science and Engineering, Springer Science and Business Media Deutschland GmbH, pp. 2183-2192, 5th International Conference on Building Energy and Environment, COBEE 2022, Montreal, Canada, 07/25/22. https://doi.org/10.1007/978-981-19-9822-5_233

A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings. / Wang, Xuezheng; Dong, Bing; Zhang, Jianshun et al.
Proceedings of the 5th International Conference on Building Energy and Environment. ed. / Liangzhu Leon Wang; Hua Ge; Mohamed Ouf; Zhiqiang John Zhai; Dahai Qi; Chanjuan Sun; Dengjia Wang. Springer Science and Business Media Deutschland GmbH, 2023. p. 2183-2192 (Environmental Science and Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wang, Xuezheng

AU - Dong, Bing

AU - Zhang, Jianshun

AU - Gupta, Bhavesh

AU - Ramirez, Moises

AU - Liu, Zhenlei

PY - 2023

Y1 - 2023

N2 - Before the COVID-19 pandemic, buildings accounted for more than 40% of the total energy. The need for improving indoor air quality (IAQ) not only during the pandemic but also in the post-pandemic era presents a unique opportunity for innovation that meets the needs in both environmental health and building energy efficiency. Carbon-dioxide concentration has been widely used for modeling and quantifying IAQ. Model predictive control (MPC) has been demonstrated promising potential in improving the energy performance of building heat ventilating and air conditioning (HVAC) systems. However, little research fell on both IAQ and energy efficiency improvement. In the paper, we developed a data-driven, coupled—IAQ and energy simulation method that combines thermal comfort and indoor air quality, specifically CO2. A new MPC algorithm was developed correspondingly to improve both energy-saving and indoor health. The results of a one-week, national-wide cooling season simulation indicate at most 50% energy savings while maintaining less than 700 PPM indoor CO2.

AB - Before the COVID-19 pandemic, buildings accounted for more than 40% of the total energy. The need for improving indoor air quality (IAQ) not only during the pandemic but also in the post-pandemic era presents a unique opportunity for innovation that meets the needs in both environmental health and building energy efficiency. Carbon-dioxide concentration has been widely used for modeling and quantifying IAQ. Model predictive control (MPC) has been demonstrated promising potential in improving the energy performance of building heat ventilating and air conditioning (HVAC) systems. However, little research fell on both IAQ and energy efficiency improvement. In the paper, we developed a data-driven, coupled—IAQ and energy simulation method that combines thermal comfort and indoor air quality, specifically CO2. A new MPC algorithm was developed correspondingly to improve both energy-saving and indoor health. The results of a one-week, national-wide cooling season simulation indicate at most 50% energy savings while maintaining less than 700 PPM indoor CO2.

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KW - Indoor air quality

KW - Model predictive control

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SN - 9789811998218

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BT - Proceedings of the 5th International Conference on Building Energy and Environment

A2 - Wang, Liangzhu Leon

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A2 - Qi, Dahai

A2 - Sun, Chanjuan

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PB - Springer Science and Business Media Deutschland GmbH

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Y2 - 25 July 2022 through 29 July 2022

ER -

Wang X, Dong B, Zhang J, Gupta B, Ramirez M, Liu Z. A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings. In Wang LL, Ge H, Ouf M, Zhai ZJ, Qi D, Sun C, Wang D, editors, Proceedings of the 5th International Conference on Building Energy and Environment. Springer Science and Business Media Deutschland GmbH. 2023. p. 2183-2192. (Environmental Science and Engineering). doi: 10.1007/978-981-19-9822-5_233

A Predictive Control Strategy to Maximize Energy Savings While Maintaining Indoor Air Quality in Commercial Buildings

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