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Energy saving by integrated control of natural ventilation and HVAC systems using model guide for comparison

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  • Homod, Raad Z.
  • Sahari, Khairul Salleh Mohamed
  • Almurib, Haider A.F.

Abstract

Integrated control by controlling both natural ventilation and HVAC systems based on human thermal comfort requirement can result in significant energy savings. The concept of this paper differs from conventional methods of energy saving in HVAC systems by integrating the control of both these HVAC systems and the available natural ventilation that is based on the temperature difference between the indoor and the outdoor air. This difference affects the rate of change of indoor air enthalpy or indoor air potential energy storage. However, this is not efficient enough as there are other factors affecting the rate of change of indoor air enthalpy that should be considered to achieve maximum energy saving. One way of improvement can be through the use of model guide for comparison (MGFC) that uses physical-empirical hybrid modelling to predict the rate of change of indoor air potential energy storage considering building fabric and its fixture. Three methods (normal, conventional and proposed) are tested on an identical residential building model using predicted mean vote (PMV) sensor as a criterion test for thermal comfort standard. The results indicate that the proposed method achieved significant energy savings compared with the other methods while still achieving thermal comfort.

Suggested Citation

  • Homod, Raad Z. & Sahari, Khairul Salleh Mohamed & Almurib, Haider A.F., 2014. "Energy saving by integrated control of natural ventilation and HVAC systems using model guide for comparison," Renewable Energy, Elsevier, vol. 71(C), pages 639-650.
    • Handle: RePEc:eee:renene:v:71:y:2014:i:c:p:639-650
    DOI: 10.1016/j.renene.2014.06.015
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    1. Kritana Prueksakorn & Cheng-Xu Piao & Hyunchul Ha & Taehyeung Kim, 2015. "Computational and Experimental Investigation for an Optimal Design of Industrial Windows to Allow Natural Ventilation during Wind-Driven Rain," Sustainability, MDPI, vol. 7(8), pages 1-22, August.
    2. 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.
    3. Homod, Raad Z., 2018. "Analysis and optimization of HVAC control systems based on energy and performance considerations for smart buildings," Renewable Energy, Elsevier, vol. 126(C), pages 49-64.
    4. Yuanda Hong & Collins I. Ezeh & Wu Deng & Sung-Hugh Hong & Zhen Peng, 2019. "Building Energy Retrofit Measures in Hot-Summer–Cold-Winter Climates: A Case Study in Shanghai," Energies, MDPI, vol. 12(17), pages 1-32, September.
    5. Homod, Raad Z. & Gaeid, Khalaf S. & Dawood, Suroor M. & Hatami, Alireza & Sahari, Khairul S., 2020. "Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings," Applied Energy, Elsevier, vol. 271(C).
    6. Homod, Raad Z. & Mohammed, Hayder Ibrahim & Abderrahmane, Aissa & Alawi, Omer A. & Khalaf, Osamah Ibrahim & Mahdi, Jasim M. & Guedri, Kamel & Dhaidan, Nabeel S. & Albahri, A.S. & Sadeq, Abdellatif M. , 2023. "Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent," Applied Energy, Elsevier, vol. 351(C).
    7. Gil-Baez, Maite & Barrios-Padura, Ángela & Molina-Huelva, Marta & Chacartegui, R., 2017. "Natural ventilation systems in 21st-century for near zero energy school buildings," Energy, Elsevier, vol. 137(C), pages 1186-1200.
    8. Carmen María Calama-González & Ángel Luis León-Rodríguez & Rafael Suárez, 2019. "Indoor Air Quality Assessment: Comparison of Ventilation Scenarios for Retrofitting Classrooms in a Hot Climate," Energies, MDPI, vol. 12(24), pages 1-20, December.
    9. Cui, X. & Mohan, B. & Islam, M.R. & Chou, S.K. & Chua, K.J., 2017. "Energy performance evaluation and application of an air treatment system for conditioning building spaces in tropics," Applied Energy, Elsevier, vol. 204(C), pages 1500-1512.
    10. Homod, Raad Z. & Togun, Hussein & Ateeq, Adnan A. & Al-Mousawi, Fadhel Noraldeen & Yaseen, Zaher Mundher & Al-Kouz, Wael & Hussein, Ahmed Kadhim & Alawi, Omer A. & Goodarzi, Marjan & Ahmadi, Goodarz, 2022. "An innovative clustering technique to generate hybrid modeling of cooling coils for energy analysis: A case study for control performance in HVAC systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    11. Abdul Mujeebu, Muhammad & Alshamrani, Othman Subhi, 2016. "Prospects of energy conservation and management in buildings – The Saudi Arabian scenario versus global trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1647-1663.
    12. He, Yueer & Liu, Meng & Kvan, Thomas & Peng, Shini, 2017. "An enthalpy-based energy savings estimation method targeting thermal comfort level in naturally ventilated buildings in hot-humid summer zones," Applied Energy, Elsevier, vol. 187(C), pages 717-731.
    13. Chenari, Behrang & Dias Carrilho, João & Gameiro da Silva, Manuel, 2016. "Towards sustainable, energy-efficient and healthy ventilation strategies in buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1426-1447.
    14. Galatioto, A. & Ciulla, G. & Ricciu, R., 2017. "An overview of energy retrofit actions feasibility on Italian historical buildings," Energy, Elsevier, vol. 137(C), pages 991-1000.
    15. Homod, Raad Z. & Togun, Hussein & Kadhim Hussein, Ahmed & Noraldeen Al-Mousawi, Fadhel & Yaseen, Zaher Mundher & Al-Kouz, Wael & Abd, Haider J. & Alawi, Omer A. & Goodarzi, Marjan & Hussein, Omar A., 2022. "Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings," Applied Energy, Elsevier, vol. 313(C).
    16. 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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