IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i10p1887-d232110.html
   My bibliography  Save this article

The Optimized Energy Saving of a Refrigerating Chamber

Author

Listed:
  • Whei-Min Lin

    (Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan)

  • Chung-Yuen Yang

    (Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan)

  • Ming-Tang Tsai

    (Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan)

  • Hong-Jey Gow

    (R&D, Kuen-Ling Machinery Refrigerating Co., Ltd., Kaohsiung 82644, Taiwan)

Abstract

This paper proposes a control strategy for the energy saving of refrigerating chambers. Combining binary coding and proteome reorganization, the binary proteome algorithm (BPA) is proposed to solve this problem. The refrigeration system model is firstly established based on the performance data of compressors and temperature measurements of each refrigerating chamber. The objective function is an averaged coefficient of performance ( COP ), which considers the switching loss of the compressors, power consumption of the compressors, and refrigerating capacity of the chambers. The control strategy is defined as an optimization problem with constraints to avoid the ineffective operation of a refrigeration system for improving the COP . BPA is adopted to solve the control strategy for optimizing energy saving. The effectiveness and efficiency of the BPA are demonstrated using a real system, and the results are compared with the original control strategy. Results show that the average power consumption drops from 115.92 kW to 108.82 kW, and the average COP value rises from 1.92 to 2.03. The proposed control strategy is feasible, robust, and more effective in energy-saving problems. Other than energy saving, the proposed control strategy also has the benefits of reducing the evaporator frost formation, which allows the products to avoid chill damage.

Suggested Citation

  • Whei-Min Lin & Chung-Yuen Yang & Ming-Tang Tsai & Hong-Jey Gow, 2019. "The Optimized Energy Saving of a Refrigerating Chamber," Energies, MDPI, vol. 12(10), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1887-:d:232110
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/10/1887/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/10/1887/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clemente García Cutillas & Javier Ruiz Ramírez & Manuel Lucas Miralles, 2017. "Optimum Design and Operation of an HVAC Cooling Tower for Energy and Water Conservation," Energies, MDPI, vol. 10(3), pages 1-27, March.
    2. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    3. Powell, Kody M. & Cole, Wesley J. & Ekarika, Udememfon F. & Edgar, Thomas F., 2013. "Optimal chiller loading in a district cooling system with thermal energy storage," Energy, Elsevier, vol. 50(C), pages 445-453.
    4. Huang, Yanjun & Khajepour, Amir & Bagheri, Farshid & Bahrami, Majid, 2016. "Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 184(C), pages 605-618.
    Full references (including those not matched with items on IDEAS)

    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. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    2. Cox, Sam J. & Kim, Dongsu & Cho, Heejin & Mago, Pedro, 2019. "Real time optimal control of district cooling system with thermal energy storage using neural networks," Applied Energy, Elsevier, vol. 238(C), pages 466-480.
    3. 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.
    4. Awais Shah & Deqing Huang & Tianpeng Huang & Umar Farid, 2018. "Optimization of BuildingsEnergy Consumption by Designing Sliding Mode Control for Multizone VAV Air Conditioning Systems," Energies, MDPI, vol. 11(11), pages 1-18, October.
    5. Jing, Gang & Cai, Wenjian & Zhang, Xin & Cui, Can & Yin, Xiaohong & Xian, Huacai, 2019. "An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system," Energy, Elsevier, vol. 172(C), pages 1053-1065.
    6. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    7. Zu, Kan & Qin, Menghao & Cui, Shuqing, 2020. "Progress and potential of metal-organic frameworks (MOFs) as novel desiccants for built environment control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    8. Mortazavi, Mehdi & Schmid, Michael & Moghaddam, Saeed, 2017. "Compact and efficient generator for low grade solar and waste heat driven absorption systems," Applied Energy, Elsevier, vol. 198(C), pages 173-179.
    9. Mahmood, Muhammad H. & Sultan, Muhammad & Miyazaki, Takahiko & Koyama, Shigeru & Maisotsenko, Valeriy S., 2016. "Overview of the Maisotsenko cycle – A way towards dew point evaporative cooling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 537-555.
    10. Adamczyk, Janusz & Dylewski, Robert, 2017. "The impact of thermal insulation investments on sustainability in the construction sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 421-429.
    11. Laslett, Dean & Carter, Craig & Creagh, Chris & Jennings, Philip, 2017. "A large-scale renewable electricity supply system by 2030: Solar, wind, energy efficiency, storage and inertia for the South West Interconnected System (SWIS) in Western Australia," Renewable Energy, Elsevier, vol. 113(C), pages 713-731.
    12. Powell, Kody M. & Kim, Jong Suk & Cole, Wesley J. & Kapoor, Kriti & Mojica, Jose L. & Hedengren, John D. & Edgar, Thomas F., 2016. "Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market," Energy, Elsevier, vol. 113(C), pages 52-63.
    13. Zu, Kan & Qin, Menghao, 2021. "Experimental and modeling investigation of water adsorption of hydrophilic carboxylate-based MOF for indoor moisture control," Energy, Elsevier, vol. 228(C).
    14. Ruparathna, Rajeev & Hewage, Kasun & Sadiq, Rehan, 2016. "Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1032-1045.
    15. Thangavelu, Sundar Raj & Myat, Aung & Khambadkone, Ashwin, 2017. "Energy optimization methodology of multi-chiller plant in commercial buildings," Energy, Elsevier, vol. 123(C), pages 64-76.
    16. Xu, Peng & Ma, Xiaoli & Zhao, Xudong & Fancey, Kevin, 2017. "Experimental investigation of a super performance dew point air cooler," Applied Energy, Elsevier, vol. 203(C), pages 761-777.
    17. Jim, C.Y., 2014. "Air-conditioning energy consumption due to green roofs with different building thermal insulation," Applied Energy, Elsevier, vol. 128(C), pages 49-59.
    18. Haitao Wang & Ning Lu & Fanghao Wu & Jianfeng Zhai, 2023. "Coupling Computational Fluid Dynamics and EnergyPlus to Optimize Energy Consumption and Comfort in Air Column Ventilation at a Tall High-Speed Rail Station," Sustainability, MDPI, vol. 15(17), pages 1-16, August.
    19. Shi, Long, 2018. "Theoretical models for wall solar chimney under cooling and heating modes considering room configuration," Energy, Elsevier, vol. 165(PB), pages 925-938.
    20. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).

    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:gam:jeners:v:12:y:2019:i:10:p:1887-:d:232110. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.