IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v264y2023ics0360544222030638.html
   My bibliography  Save this article

Model predictive control of a thermal chimney and dynamic solar shades for an all-glass facades building

Author

Listed:
  • de Araujo Passos, Luigi Antonio
  • Ceha, Thomas Joseph
  • Baldi, Simone
  • De Schutter, Bart

Abstract

Controlling the operation of HVAC (Heating, Ventilation, and Air-Conditioning) systems is arguably the most effective way to reach desired indoor conditions in buildings. Nevertheless, such control may involve complex dynamics when dealing with passive energy technologies. In this paper, we focus on maximizing the passive operation of HVAC in a novel low-energy building design by means of Model Predictive Control (MPC). The low-energy building design, located in The Green Village, consists of a thermal chimney and solar shades over all-glass facades to provide the required indoor air conditioning as passively as possible. The MPC controller is based on a transient grey box model and a hierarchical control architecture to satisfy thermal comfort while minimizing the active energy requirements. Using sensor data collected from the actual building in April and May 2021, the grey box model shows a good agreement with the measurements, since the variance accounted for is 90% in most cases. Moreover, via a comparative study among different MPC architectures we show that managing the distinct transient response of each component (shades and chimney) is the best for successful overall performance – e.g. considering linear agents for shading and nonlinear agents for ventilation. The hierarchical MPC architecture established outperforms the standard ones by 22.7% in terms of control performance. We also compare the proposed MPC approach against the rule-based control method currently implemented in the actual building, which indicates that MPC demands about 78% less active energy, highlighting the proposed optimization-based control approach.

Suggested Citation

  • de Araujo Passos, Luigi Antonio & Ceha, Thomas Joseph & Baldi, Simone & De Schutter, Bart, 2023. "Model predictive control of a thermal chimney and dynamic solar shades for an all-glass facades building," Energy, Elsevier, vol. 264(C).
    • Handle: RePEc:eee:energy:v:264:y:2023:i:c:s0360544222030638
    DOI: 10.1016/j.energy.2022.126177
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222030638
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.126177?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. Zhang, Yi & Tennakoon, Thilhara & Chan, Yin Hoi & Chan, Ka Chung & Fu, Sau Chung & Tso, Chi Yan & Yu, Kin Man & Huang, Bao Ling & Yao, Shu Huai & Qiu, Hui He & Chao, Christopher Y.H., 2022. "Energy consumption modelling of a passive hybrid system for office buildings in different climates," Energy, Elsevier, vol. 239(PA).
    2. Zhang, Haihua & Yang, Dong & Tam, Vivian W.Y. & Tao, Yao & Zhang, Guomin & Setunge, Sujeeva & Shi, Long, 2021. "A critical review of combined natural ventilation techniques in sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    3. Chi, Fang'ai & Wang, Ruonan & Li, Gaomei & Xu, Liming & Wang, Yonghe & Peng, Changhai, 2020. "Integration of sun-tracking shading panels into window system towards maximum energy saving and non-glare daylighting," Applied Energy, Elsevier, vol. 260(C).
    4. Joe, Jaewan & Karava, Panagiota, 2019. "A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings," Applied Energy, Elsevier, vol. 245(C), pages 65-77.
    5. Monghasemi, Nima & Vadiee, Amir, 2018. "A review of solar chimney integrated systems for space heating and cooling application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2714-2730.
    6. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Xue, Xizhen & Lin, Zhongwei & Fang, Fang, 2021. "Real-time optimal operation of integrated electricity and heat system considering reserve provision of large-scale heat pumps," Energy, Elsevier, vol. 237(C).
    7. Chen, Yujiao & Tong, Zheming & Wu, Wentao & Samuelson, Holly & Malkawi, Ali & Norford, Leslie, 2019. "Achieving natural ventilation potential in practice: Control schemes and levels of automation," Applied Energy, Elsevier, vol. 235(C), pages 1141-1152.
    8. Yang, Shiyu & Wan, Man Pun & Ng, Bing Feng & Dubey, Swapnil & Henze, Gregor P. & Chen, Wanyu & Baskaran, Krishnamoorthy, 2021. "Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems," Applied Energy, Elsevier, vol. 297(C).
    9. Wang, Ran & Feng, Wei & Wang, Lan & Lu, Shilei, 2021. "A comprehensive evaluation of zero energy buildings in cold regions: Actual performance and key technologies of cases from China, the US, and the European Union," Energy, Elsevier, vol. 215(PA).
    10. Zhan, Sicheng & Chong, Adrian, 2021. "Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    11. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    12. Zhou, Yuan & Wang, Jiangjiang & Liu, Yi & Yan, Rujing & Ma, Yanpeng, 2021. "Incorporating deep learning of load predictions to enhance the optimal active energy management of combined cooling, heating and power system," Energy, Elsevier, vol. 233(C).
    13. Chen, Ke & Pan, Ming, 2021. "Operation optimization of combined cooling, heating, and power superstructure system for satisfying demand fluctuation," Energy, Elsevier, vol. 237(C).
    14. Lankeshwara, Gayan & Sharma, Rahul & Yan, Ruifeng & Saha, Tapan K., 2022. "A hierarchical control scheme for residential air-conditioning loads to provide real-time market services under uncertainties," Energy, Elsevier, vol. 250(C).
    15. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cui, Can & Xue, Jing, 2024. "Energy and comfort aware operation of multi-zone HVAC system through preference-inspired deep reinforcement learning," Energy, Elsevier, vol. 292(C).
    2. Blaud, Pierre Clement & Haurant, Pierrick & Chevrel, Philippe & Claveau, Fabien & Mouraud, Anthony, 2023. "Multi-flow optimization of a greenhouse system: A hierarchical control approach," Applied Energy, Elsevier, vol. 351(C).

    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. Balali, Amirhossein & Yunusa-Kaltungo, Akilu & Edwards, Rodger, 2023. "A systematic review of passive energy consumption optimisation strategy selection for buildings through multiple criteria decision-making techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    2. Kang, Yiting & Zhang, Dongjie & Cui, Yu & Xu, Wei & Lu, Shilei & Wu, Jianlin & Hu, Yiqun, 2024. "Integrated passive design method optimized for carbon emissions, economics, and thermal comfort of zero-carbon buildings," Energy, Elsevier, vol. 295(C).
    3. Wang, Dengjia & Hu, Liang & Du, Hu & Liu, Yanfeng & Huang, Jianxiang & Xu, Yanchao & Liu, Jiaping, 2020. "Classification, experimental assessment, modeling methods and evaluation metrics of Trombe walls," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. Li, Hangxin & Wang, Shengwei, 2022. "Comparative assessment of alternative MPC strategies using real meteorological data and their enhancement for optimal utilization of flexibility-resources in buildings," Energy, Elsevier, vol. 244(PA).
    5. Elnour, Mariam & Himeur, Yassine & Fadli, Fodil & Mohammedsherif, Hamdi & Meskin, Nader & Ahmad, Ahmad M. & Petri, Ioan & Rezgui, Yacine & Hodorog, Andrei, 2022. "Neural network-based model predictive control system for optimizing building automation and management systems of sports facilities," Applied Energy, Elsevier, vol. 318(C).
    6. Yang, Shiyu & Oliver Gao, H. & You, Fengqi, 2022. "Model predictive control for Demand- and Market-Responsive building energy management by leveraging active latent heat storage," Applied Energy, Elsevier, vol. 327(C).
    7. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "Impact of adjustment strategies on building design process in different climates oriented by multiple performance," Applied Energy, Elsevier, vol. 266(C).
    8. Zhang, Haihua & Tao, Yao & Zhang, Guomin & Li, Jie & Setunge, Sujeeva & Shi, Long, 2022. "Impacts of storey number of buildings on solar chimney performance: A theoretical and numerical approach," Energy, Elsevier, vol. 261(PA).
    9. Choi, Kwangwon & Lee, Donggun & Park, Semi & Joe, Jaewan, 2024. "Infrared signal-based implementation of model-based predictive control (MPC) for cost saving in a campus building," Energy, Elsevier, vol. 306(C).
    10. Liu, Xiaoqi & Lee, Seungjae & Bilionis, Ilias & Karava, Panagiota & Joe, Jaewan & Sadeghi, Seyed Amir, 2021. "A user-interactive system for smart thermal environment control in office buildings," Applied Energy, Elsevier, vol. 298(C).
    11. Andrzej Ożadowicz & Gabriela Walczyk, 2023. "Energy Performance and Control Strategy for Dynamic Façade with Perovskite PV Panels—Technical Analysis and Case Study," Energies, MDPI, vol. 16(9), pages 1-23, April.
    12. Ana Mafalda Matos & João M. P. Q. Delgado & Ana Sofia Guimarães, 2022. "Energy-Efficiency Passive Strategies for Mediterranean Climate: An Overview," Energies, MDPI, vol. 15(7), pages 1-20, April.
    13. Sun, Hongchang & Niu, Yanlei & Li, Chengdong & Zhou, Changgeng & Zhai, Wenwen & Chen, Zhe & Wu, Hao & Niu, Lanqiang, 2022. "Energy consumption optimization of building air conditioning system via combining the parallel temporal convolutional neural network and adaptive opposition-learning chimp algorithm," Energy, Elsevier, vol. 259(C).
    14. Liu, Mingzhe & Guo, Mingyue & Fu, Yangyang & O’Neill, Zheng & Gao, Yuan, 2024. "Expert-guided imitation learning for energy management: Evaluating GAIL’s performance in building control applications," Applied Energy, Elsevier, vol. 372(C).
    15. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
    16. 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.
    17. Shuiguang Tong & Xiang Zhang & Zheming Tong & Yanling Wu & Ning Tang & Wei Zhong, 2019. "Online Ash Fouling Prediction for Boiler Heating Surfaces based on Wavelet Analysis and Support Vector Regression," Energies, MDPI, vol. 13(1), pages 1-20, December.
    18. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    19. Dong, Zihang & Zhang, Xi & Li, Yijun & Strbac, Goran, 2023. "Values of coordinated residential space heating in demand response provision," Applied Energy, Elsevier, vol. 330(PB).
    20. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).

    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:energy:v:264:y:2023:i:c:s0360544222030638. 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.journals.elsevier.com/energy .

    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.