IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v287y2021ics0306261921000866.html
   My bibliography  Save this article

A model-based multi-objective optimization of energy consumption and thermal comfort for active chilled beam systems

Author

Listed:
  • Wu, Bingjie
  • Cai, Wenjian
  • Chen, Haoran

Abstract

Active chilled beam (ACB) systems provide two highly-coupled cooling capacities due to its unique structure through combining primary air nozzle and cooling coil, whose energy consumption is difficult to be estimated and balanced against thermal comfort. This study considered the trade-off between energy consumption and thermal comfort as a multi-objective optimization problem and proposed a novel and practical solution by utilizing empirical energy models of the ACB system and an evolutional non-dominated sorting genetic algorithm II. The energy models are established for components of fans, pumps, and chillers based on fundamental equations which are validated by experimental data. The thermal comfort of each room is quantified by the predicted percentage dissatisfied (PPD) model. Chilled water flow rate, primary airflow rate, and room temperature in ACB systems are specifically chosen as control variables due to the control convenience. Besides, a parameterless selection strategy that considers both thermal comfort and energy consumption is proposed to select the most appropriate solution among Pareto optimal solutions. Three steady-state experiments with different heat load conditions are conducted. Compared to experienced operation, the proposed strategy demonstrates a maximum of 39.32% of energy saving and 12.21% of PPD reduction by increasing the water flow rate and room temperature, and reducing the primary airflow rate. Furthermore, this study investigates the distribution of capacities in ACB systems and suggests to assign more capacity to the cooling coil based on energy efficiency considerations. A good trade-off is achieved between energy consumption and thermal comfort through the proposed multi-objective optimization strategy.

Suggested Citation

  • Wu, Bingjie & Cai, Wenjian & Chen, Haoran, 2021. "A model-based multi-objective optimization of energy consumption and thermal comfort for active chilled beam systems," Applied Energy, Elsevier, vol. 287(C).
  • Handle: RePEc:eee:appene:v:287:y:2021:i:c:s0306261921000866
    DOI: 10.1016/j.apenergy.2021.116531
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921000866
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.116531?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    2. Zhang, Sheng & Cheng, Yong & Liu, Jian & Lin, Zhang, 2019. "Subzone control optimization of air distribution for thermal comfort and energy efficiency under cooling load uncertainty," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Chen, Can & Cai, Wenjian & Giridharan, Karunagaran & Wang, Youyi, 2014. "A hybrid dynamic modeling of active chilled beam terminal unit," Applied Energy, Elsevier, vol. 128(C), pages 133-143.
    4. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    5. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    6. Khoroshiltseva, Marina & Slanzi, Debora & Poli, Irene, 2016. "A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices," Applied Energy, Elsevier, vol. 184(C), pages 1400-1410.
    7. Chen, Qun & Wang, Yi-Fei & Xu, Yun-Chao, 2015. "A thermal resistance-based method for the optimal design of central variable water/air volume chiller systems," Applied Energy, Elsevier, vol. 139(C), pages 119-130.
    8. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    9. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    10. Zhang, Sheng & Cheng, Yong & Fang, Zhaosong & Huan, Chao & Lin, Zhang, 2017. "Optimization of room air temperature in stratum-ventilated rooms for both thermal comfort and energy saving," Applied Energy, Elsevier, vol. 204(C), pages 420-431.
    11. Kim, Jimin & Hong, Taehoon & Jeong, Jaemin & Koo, Choongwan & Jeong, Kwangbok, 2016. "An optimization model for selecting the optimal green systems by considering the thermal comfort and energy consumption," Applied Energy, Elsevier, vol. 169(C), pages 682-695.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chaudhuri, Tanaya & Soh, Yeng Chai & Li, Hua & Xie, Lihua, 2019. "A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings," Applied Energy, Elsevier, vol. 248(C), pages 44-53.
    2. Amir Faraji & Maria Rashidi & Fatemeh Rezaei & Payam Rahnamayiezekavat, 2023. "A Meta-Synthesis Review of Occupant Comfort Assessment in Buildings (2002–2022)," Sustainability, MDPI, vol. 15(5), pages 1-36, February.
    3. Cui, X. & Islam, M.R. & Chua, K.J., 2019. "Experimental study and energy saving potential analysis of a hybrid air treatment cooling system in tropical climates," Energy, Elsevier, vol. 172(C), pages 1016-1026.
    4. Lee, Minjung & Ham, Jeonggyun & Lee, Jeong-Won & Cho, Honghyun, 2023. "Analysis of thermal comfort, energy consumption, and CO2 reduction of indoor space according to the type of local heating under winter rest conditions," Energy, Elsevier, vol. 268(C).
    5. Rabani, Mehrdad & Bayera Madessa, Habtamu & Mohseni, Omid & Nord, Natasa, 2020. "Minimizing delivered energy and life cycle cost using Graphical script: An office building retrofitting case," Applied Energy, Elsevier, vol. 268(C).
    6. Azar, Elie & Nikolopoulou, Christina & Papadopoulos, Sokratis, 2016. "Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling," Applied Energy, Elsevier, vol. 183(C), pages 926-937.
    7. O'Grady, Małgorzata & Lechowska, Agnieszka A. & Harte, Annette M., 2017. "Quantification of heat losses through building envelope thermal bridges influenced by wind velocity using the outdoor infrared thermography technique," Applied Energy, Elsevier, vol. 208(C), pages 1038-1052.
    8. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
    9. Liu, Zhongbing & Zhang, Yelin & Zhang, Ling & Luo, Yongqiang & Wu, Zhenghong & Wu, Jing & Yin, Yingde & Hou, Guoqing, 2018. "Modeling and simulation of a photovoltaic thermal-compound thermoelectric ventilator system," Applied Energy, Elsevier, vol. 228(C), pages 1887-1900.
    10. Haider Latif & Samira Rahnama & Alessandro Maccarini & Goran Hultmark & Peter V. Nielsen & Alireza Afshari, 2022. "Precision Ventilation in an Open-Plan Office: A New Application of Active Chilled Beam (ACB) with a JetCone Feature," Sustainability, MDPI, vol. 14(7), pages 1-17, April.
    11. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    12. Mehrdad Rabani & Habtamu Bayera Madessa & Natasa Nord, 2021. "Building Retrofitting through Coupling of Building Energy Simulation-Optimization Tool with CFD and Daylight Programs," Energies, MDPI, vol. 14(8), pages 1-23, April.
    13. Olszewski, Pawel, 2022. "Experimental analysis of ON/OFF and variable speed drive controlled industrial chiller towards energy efficient operation," Applied Energy, Elsevier, vol. 309(C).
    14. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
    15. Pamulapati, Trinadh & Mallipeddi, Rammohan & Lee, Minho, 2020. "Multi-objective home appliance scheduling with implicit and interactive user satisfaction modelling," Applied Energy, Elsevier, vol. 267(C).
    16. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    17. Kim, Jimin & Hong, Taehoon & Jeong, Jaemin & Lee, Myeonghwi & Lee, Minhyun & Jeong, Kwangbok & Koo, Choongwan & Jeong, Jaewook, 2017. "Establishment of an optimal occupant behavior considering the energy consumption and indoor environmental quality by region," Applied Energy, Elsevier, vol. 204(C), pages 1431-1443.
    18. Katerina Sojkova & Martin Volf & Antonin Lupisek & Roman Bolliger & Tomas Vachal, 2019. "Selection of Favourable Concept of Energy Retrofitting Solution for Social Housing in the Czech Republic Based on Economic Parameters, Greenhouse Gases, and Primary Energy Consumption," Sustainability, MDPI, vol. 11(22), pages 1-26, November.
    19. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
    20. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:287:y:2021:i:c:s0306261921000866. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.