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Fuzzy control system for thermal and visual comfort in building

Author

Listed:
  • Kristl, Živa
  • Košir, Mitja
  • Trobec Lah, Mateja
  • Krainer, Aleš

Abstract

In the era of informational and technological breakthrough, the automatically controlled living and working environment is expected to become a commonly used service. This paper deals with dynamically controlled thermal and illumination responses of built environment in real-time conditions. The aim is to harmonize thermal and optical behaviour of a building by coordinating energy flows that pass through the transparent part of the envelope. For this purpose, a test chamber with an opening on the southern side was built. Changeable geometry of the opening is achieved by the automated external roller blind. A fuzzy control system enables the positioning of the shading device according to the desired indoor set points and the outdoor conditions. Through the experiments, the fuzzy controllers were tuned and gradually improved. Some sets of the experiments are presented here to illustrate the process.

Suggested Citation

  • Kristl, Živa & Košir, Mitja & Trobec Lah, Mateja & Krainer, Aleš, 2008. "Fuzzy control system for thermal and visual comfort in building," Renewable Energy, Elsevier, vol. 33(4), pages 694-702.
    • Handle: RePEc:eee:renene:v:33:y:2008:i:4:p:694-702
    DOI: 10.1016/j.renene.2007.03.020
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    Citations

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    Cited by:

    1. Gago, E.J. & Muneer, T. & Knez, M. & Köster, H., 2015. "Natural light controls and guides in buildings. Energy saving for electrical lighting, reduction of cooling load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1-13.
    2. Homod, Raad Z., 2014. "Assessment regarding energy saving and decoupling for different AHU (air handling unit) and control strategies in the hot-humid climatic region of Iraq," Energy, Elsevier, vol. 74(C), pages 762-774.
    3. Kim, Wonuk & Jeon, Yongseok & Kim, Yongchan, 2016. "Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method," Applied Energy, Elsevier, vol. 162(C), pages 666-674.
    4. 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).
    5. Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2018. "Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps," Energies, MDPI, vol. 11(3), pages 1-41, February.
    6. Baloch, Ashfaque Ahmed & Shaikh, Pervez Hameed & Shaikh, Faheemullah & Leghari, Zohaib Hussain & Mirjat, Nayyar Hussain & Uqaili, Muhammad Aslam, 2018. "Simulation tools application for artificial lighting in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3007-3026.
    7. Taesub Lim & Woong Seog Yim & Daeung Danny Kim, 2020. "Evaluation of Daylight and Cooling Performance of Shading Devices in Residential Buildings in South Korea," Energies, MDPI, vol. 13(18), pages 1-14, September.
    8. Yan, Huaxia & Pan, Yan & Li, Zhao & Deng, Shiming, 2018. "Further development of a thermal comfort based fuzzy logic controller for a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 219(C), pages 312-324.
    9. Esmail Mahmoudi Saber & Issa Chaer & Aaron Gillich & Bukola Grace Ekpeti, 2021. "Review of Intelligent Control Systems for Natural Ventilation as Passive Cooling Strategy for UK Buildings and Similar Climatic Conditions," Energies, MDPI, vol. 14(15), pages 1-16, July.

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