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HVAC System Control Solutions Based on Modern IT Technologies: A Review Article

Author

Listed:
  • Anatolijs Borodinecs

    (Department of Heat Engineering and Technology, Riga Technical University, Kipsalas Street 6 A, LV-1048 Riga, Latvia)

  • Jurgis Zemitis

    (Department of Heat Engineering and Technology, Riga Technical University, Kipsalas Street 6 A, LV-1048 Riga, Latvia)

  • Arturs Palcikovskis

    (Department of Heat Engineering and Technology, Riga Technical University, Kipsalas Street 6 A, LV-1048 Riga, Latvia)

Abstract

As energy consumption for building engineering systems is a major part of the total energy spent, it is necessary to reduce it. This leads to the need for the development of new solutions for the control of heating, ventilation, and conditioning (HVAC) systems that are responsive to humans and their demands. In this review article, the existing research and technology advancements of the modern technologies of computer vision and neural networks for application in HVAC control systems are studied. Objectives such as human detection and location, human activity monitoring, skin temperature detection, and clothing level detection systems are important for the operation of precise, high-tech HVAC systems. This article tries to compile the latest achievements and principal solutions on how this information is acquired. Moreover, it how parameters such as indoor air quality (IAQ), variable air volume ventilation, computer vision, metabolic rate, and human clothing isolation can affect final energy consumption is studied. The research studies discussed in this review article have been tested in real application scenarios and prove the benefits of using a particular technology in ventilation systems. As a result, the modernized control systems have shown advantages over the currently applied typical non-automated systems by providing higher IAQ and reducing unnecessary energy consumption.

Suggested Citation

  • Anatolijs Borodinecs & Jurgis Zemitis & Arturs Palcikovskis, 2022. "HVAC System Control Solutions Based on Modern IT Technologies: A Review Article," Energies, MDPI, vol. 15(18), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6726-:d:914984
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    References listed on IDEAS

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    1. Renars Millers & Aleksandrs Korjakins & Arturs Lešinskis & Anatolijs Borodinecs, 2020. "Cooling Panel with Integrated PCM Layer: A Verified Simulation Study," Energies, MDPI, vol. 13(21), pages 1-20, November.
    2. Buratti, C. & Palladino, D. & Ricciardi, P., 2016. "Application of a new 13-value thermal comfort scale to moderate environments," Applied Energy, Elsevier, vol. 180(C), pages 859-866.
    3. Akinkunmi Adegbenro & Michael Short & Claudio Angione, 2021. "An Integrated Approach to Adaptive Control and Supervisory Optimisation of HVAC Control Systems for Demand Response Applications," Energies, MDPI, vol. 14(8), pages 1-18, April.
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    Cited by:

    1. Hyang-A Park & Gilsung Byeon & Wanbin Son & Jongyul Kim & Sungshin Kim, 2023. "Data-Driven Modeling of HVAC Systems for Operation of Virtual Power Plants Using a Digital Twin," Energies, MDPI, vol. 16(20), pages 1-14, October.

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