IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v87y2010i4p1158-1175.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(09)00346-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Liang, Xia & Chan, M.Y. & Shiming, Deng, 2008. "Development of a method for calculating steady-state equipment sensible heat ratio of direct expansion air conditioning units," Applied Energy, Elsevier, vol. 85(12), pages 1198-1207, December.
    2. Shahnawaz Ahmed, S. & Shah Majid, Md. & Novia, Hendri & Abd Rahman, Hasimah, 2007. "Fuzzy logic based energy saving technique for a central air conditioning system," Energy, Elsevier, vol. 32(7), pages 1222-1234.
    3. Chowdhury, Ashfaque Ahmed & Rasul, M.G. & Khan, M.M.K., 2008. "Thermal-comfort analysis and simulation for various low-energy cooling-technologies applied to an office building in a subtropical climate," Applied Energy, Elsevier, vol. 85(6), pages 449-462, June.
    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. 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. Spandagos, Constantine & Ng, Tze Ling, 2018. "Fuzzy model of residential energy decision-making considering behavioral economic concepts," Applied Energy, Elsevier, vol. 213(C), pages 611-625.
    4. 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.
    5. 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.
    6. 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.
    7. Yan, Huaxia & Xia, Yudong & Deng, Shiming, 2017. "Simulation study on a three-evaporator air conditioning system for simultaneous indoor air temperature and humidity control," Applied Energy, Elsevier, vol. 207(C), pages 294-304.
    8. 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.
    9. Ren, Zhengen & Chen, Dong, 2018. "Modelling study of the impact of thermal comfort criteria on housing energy use in Australia," Applied Energy, Elsevier, vol. 210(C), pages 152-166.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Esmaeilzadeh, Ahmad & Deal, Brian & Yousefi-Koma, Aghil & Zakerzadeh, Mohammad Reza, 2023. "How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S," Energy, Elsevier, vol. 263(PD).
    17. Chen, Wenjing & Chan, Ming-yin & Weng, Wenbing & Yan, Huaxia & Deng, Shiming, 2018. "An experimental study on the operational characteristics of a direct expansion based enhanced dehumidification air conditioning system," Applied Energy, Elsevier, vol. 225(C), pages 922-933.
    18. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    19. Liang Xie & Lai Fan & Dayu Zhang & Jixin Liu, 2023. "Passive Energy Conservation Strategies for Mitigating Energy Consumption and Reducing CO 2 Emissions in Traditional Dwellings of Peking Area, China," Sustainability, MDPI, vol. 15(23), pages 1-24, November.
    20. 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.
    21. 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.
    22. Wang, Huan & Liang, Chenjiyu & Wang, Guijin & Li, Xianting, 2024. "Energy-saving potential of fresh air management using camera-based indoor occupancy positioning system in public open space," Applied Energy, Elsevier, vol. 356(C).
    23. 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.
    24. Wei Wang & Xiaofang Shan & Syed Asad Hussain & Changshan Wang & Ying Ji, 2020. "Comparison of Multi-Control Strategies for the Control of Indoor Air Temperature and CO 2 with OpenModelica Modeling," Energies, MDPI, vol. 13(17), pages 1-20, August.
    25. 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.

    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. 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.
    2. Hong, Gui-Bing & Ma, Chih-Ming & Chen, Hua-Wei & Chuang, Kai-Jen & Chang, Chang-Tang & Su, Te-Li, 2011. "Energy flow analysis in pulp and paper industry," Energy, Elsevier, vol. 36(5), pages 3063-3068.
    3. Mohammed Awad Abuhussain & Nedhal Al-Tamimi & Badr S. Alotaibi & Manoj Kumar Singh & Sanjay Kumar & Rana Elnaklah, 2022. "Impact of Courtyard Concept on Energy Efficiency and Home Privacy in Saudi Arabia," Energies, MDPI, vol. 15(15), pages 1-18, August.
    4. Ascione, Fabrizio & Bianco, Nicola & de’ Rossi, Filippo & Turni, Gianluca & Vanoli, Giuseppe Peter, 2013. "Green roofs in European climates. Are effective solutions for the energy savings in air-conditioning?," Applied Energy, Elsevier, vol. 104(C), pages 845-859.
    5. Wang, Zhe & Hong, Tianzhen, 2020. "Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    6. Ismail Abdul Rahman & Jouvan Chandra Pratama Putra & Ade Asmi, 2014. "Modelling of Particle Dispersion in Mechanically Ventilated Space," Modern Applied Science, Canadian Center of Science and Education, vol. 8(3), pages 1-60, June.
    7. Yan, Huaxia & Xia, Yudong & Deng, Shiming, 2017. "Simulation study on a three-evaporator air conditioning system for simultaneous indoor air temperature and humidity control," Applied Energy, Elsevier, vol. 207(C), pages 294-304.
    8. Ge, Gaoming & Xiao, Fu & Xu, Xinhua, 2011. "Model-based optimal control of a dedicated outdoor air-chilled ceiling system using liquid desiccant and membrane-based total heat recovery," Applied Energy, Elsevier, vol. 88(11), pages 4180-4190.
    9. Satish Suresh Tanavade & Ganesh Nagraj Patil & C. V. Sudhir & A. M. Saravanan, 2023. "Strategic Energy Management and Carbon Footprint Reduction in University Campuses: A Comprehensive Review," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 15-27, November.
    10. Yildiz, Abdullah & Güngör, Ali, 2009. "Energy and exergy analyses of space heating in buildings," Applied Energy, Elsevier, vol. 86(10), pages 1939-1948, October.
    11. Ghahramani, Ali & Castro, Guillermo & Karvigh, Simin Ahmadi & Becerik-Gerber, Burcin, 2018. "Towards unsupervised learning of thermal comfort using infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 41-49.
    12. Taleb, Hanan M. & Sharples, Steve, 2011. "Developing sustainable residential buildings in Saudi Arabia: A case study," Applied Energy, Elsevier, vol. 88(1), pages 383-391, January.
    13. Ganesh Nagraj Patil & Satish Suresh Tanavade, 2024. "Eco-Friendly Energy Efficient Classrooms and Sustainable Campus Strategies: A Case Study on Energy Management and Carbon Footprint Reduction," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 188-197, May.
    14. Radhi, Hassan & Eltrapolsi, Ali & Sharples, Stephen, 2009. "Will energy regulations in the Gulf States make buildings more comfortable - A scoping study of residential buildings," Applied Energy, Elsevier, vol. 86(12), pages 2531-2539, December.
    15. Qi, Ronghui & Lu, Lin & Yang, Hongxing & Qin, Fei, 2013. "Investigation on wetted area and film thickness for falling film liquid desiccant regeneration system," Applied Energy, Elsevier, vol. 112(C), pages 93-101.
    16. Ahmed, S.F. & Khan, M.M.K. & Amanullah, M.T.O. & Rasul, M.G. & Hassan, N.M.S., 2021. "A parametric analysis of the cooling performance of vertical earth-air heat exchanger in a subtropical climate," Renewable Energy, Elsevier, vol. 172(C), pages 350-367.
    17. Abdul Mujeebu, Muhammad & Ashraf, Noman & Alsuwayigh, Abdulkarim H., 2016. "Effect of nano vacuum insulation panel and nanogel glazing on the energy performance of office building," Applied Energy, Elsevier, vol. 173(C), pages 141-151.
    18. Zhang, Tiantian & Tan, Yufei & Yang, Hongxing & Zhang, Xuedan, 2016. "The application of air layers in building envelopes: A review," Applied Energy, Elsevier, vol. 165(C), pages 707-734.
    19. Khan, Muhammad Waqas & Choudhry, Mohammad Ahmad & Zeeshan, Muhammad & Ali, Ahsan, 2015. "Adaptive fuzzy multivariable controller design based on genetic algorithm for an air handling unit," Energy, Elsevier, vol. 81(C), pages 477-488.
    20. Barbeito, Inés & Zaragoza, Sonia & Tarrío-Saavedra, Javier & Naya, Salvador, 2017. "Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data," Applied Energy, Elsevier, vol. 190(C), pages 1-17.

    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:appene:v:87:y:2010:i:4:p:1158-1175. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.