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Energy efficient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings

Author

Listed:
  • Karunakaran, R.
  • Iniyan, S.
  • Goic, Ranko

Abstract

Energy conservative building design has triggered greater interests in developing flexible and sophisticated air conditioning systems capable of achieving enhanced energy-savings potential without sacrificing the desired thermal comfort and indoor air quality (IAQ). This research work greatly aimed at achieving enhanced energy conservation, good thermal comfort and better IAQ for space conditioning with the application of combined variable refrigerant volume (VRV) and variable air volume (VAV) air conditioning (A/C) systems. Experimental investigation on the proposed combined air conditioning system with the application of intelligent fuzzy logic controller was performed for summer and winter climatic conditions to substantiate the energy-savings capability. The proposed system experimentally analyzed under fixed ventilation, demand controlled ventilation (DCV) and combined DCV and economizer cycle (EC) ventilation techniques effectively conserved 44% and 63% of per day average energy-savings in summer and winter design conditions respectively, while compared to the conventional constant air volume (CAV) A/C system. The results of the present investigation have proved that the proposed combined air conditioning system operated under the different ventilation strategies and controlled by the intelligent fuzzy logic controller (FLC) can be considered as an efficient technology to achieve good thermal comfort, IAQ and energy conservation in the modern heating, ventilation and air conditioning (HVAC) applications.

Suggested Citation

  • Karunakaran, R. & Iniyan, S. & Goic, Ranko, 2010. "Energy efficient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings," Applied Energy, Elsevier, vol. 87(4), pages 1158-1175, April.
  • Handle: RePEc:eee:appene:v:87:y:2010:i:4:p:1158-1175
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    References listed on IDEAS

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    Cited by:

    1. Sehar, Fakeha & Pipattanasomporn, Manisa & Rahman, Saifur, 2016. "A peak-load reduction computing tool sensitive to commercial building environmental preferences," Applied Energy, Elsevier, vol. 161(C), pages 279-289.
    2. Baldi, Simone & Michailidis, Iakovos & Ravanis, Christos & Kosmatopoulos, Elias B., 2015. "Model-based and model-free “plug-and-play” building energy efficient control," Applied Energy, Elsevier, vol. 154(C), pages 829-841.
    3. Yu, Xinqiao & Yan, Da & Sun, Kaiyu & Hong, Tianzhen & Zhu, Dandan, 2016. "Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings," Applied Energy, Elsevier, vol. 183(C), pages 725-736.
    4. Yang, Zheng & Becerik-Gerber, Burcin, 2015. "A model calibration framework for simultaneous multi-level building energy simulation," Applied Energy, Elsevier, vol. 149(C), pages 415-431.
    5. Parameshwaran, R. & Kalaiselvam, S. & Harikrishnan, S. & Elayaperumal, A., 2012. "Sustainable thermal energy storage technologies for buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2394-2433.
    6. repec:eee:appene:v:207:y:2017:i:c:p:294-304 is not listed on IDEAS
    7. Bulut, Hüsamettin & Aktacir, Mehmet Azmi, 2011. "Determination of free cooling potential: A case study for Istanbul, Turkey," Applied Energy, Elsevier, vol. 88(3), pages 680-689, March.
    8. repec:eee:appene:v:210:y:2018:i:c:p:152-166 is not listed on IDEAS
    9. Okochi, Godwine Swere & Yao, Ye, 2016. "A review of recent developments and technological advancements of variable-air-volume (VAV) air-conditioning systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 784-817.
    10. Lü, Xiaoshu & Lu, Tao & Kibert, Charles J. & Viljanen, Martti, 2014. "A novel dynamic modeling approach for predicting building energy performance," Applied Energy, Elsevier, vol. 114(C), pages 91-103.
    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. Li, Guannan & Hu, Yunpeng & Chen, Huanxin & Li, Haorong & Hu, Min & Guo, Yabin & Liu, Jiangyan & Sun, Shaobo & Sun, Miao, 2017. "Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions," Applied Energy, Elsevier, vol. 185(P1), pages 846-861.
    13. Antonopoulos, K.A. & Gioti, F. & Tzivanidis, C., 2010. "A transient model for the energy analysis of indoor spaces," Applied Energy, Elsevier, vol. 87(10), pages 3084-3091, October.
    14. Marinakis, Vangelis & Doukas, Haris & Karakosta, Charikleia & Psarras, John, 2013. "An integrated system for buildings’ energy-efficient automation: Application in the tertiary sector," Applied Energy, Elsevier, vol. 101(C), pages 6-14.
    15. 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.
    16. Zhang, Xinxin & Kobayashi, Noriyuki & He, Maogang & Wang, Jingfu, 2016. "An organic group contribution approach to radiative efficiency estimation of organic working fluid," Applied Energy, Elsevier, vol. 162(C), pages 1205-1210.
    17. Tzivanidis, C. & Antonopoulos, K.A. & Gioti, F., 2011. "Numerical simulation of cooling energy consumption in connection with thermostat operation mode and comfort requirements for the Athens buildings," Applied Energy, Elsevier, vol. 88(8), pages 2871-2884, August.
    18. Yang, YauBin & Wu, Min-Der & Chang, Yu-Choung, 2014. "Temperature control of the four-zone split inverter air conditioners using LMI expression based on LQR for mixed H2/H∞," Applied Energy, Elsevier, vol. 113(C), pages 912-923.

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