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Cooperative Optimization of A Refrigeration System with A Water-Cooled Chiller and Air-Cooled Heat Pump by Coupling BPNN and PSO

Author

Listed:
  • Qinli Deng

    (School of Civil Engineering and Architecture, Wuhan University of Technology, No.122 Luoshi Road, Wuhan 430070, China
    Hainan Institute of Wuhan University of Technology, No.5 Chuangxin Road, Yazhou District, Sanya 572024, China)

  • Liangxin Xu

    (School of Civil Engineering and Architecture, Wuhan University of Technology, No.122 Luoshi Road, Wuhan 430070, China)

  • Tingfang Zhao

    (School of Civil Engineering and Architecture, Wuhan University of Technology, No.122 Luoshi Road, Wuhan 430070, China)

  • Xuexin Hong

    (Wuhan University of Technology Design and Research Institute Co., Ltd., Wuhan 430070, China)

  • Xiaofang Shan

    (School of Civil Engineering and Architecture, Wuhan University of Technology, No.122 Luoshi Road, Wuhan 430070, China
    Hainan Institute of Wuhan University of Technology, No.5 Chuangxin Road, Yazhou District, Sanya 572024, China)

  • Zhigang Ren

    (School of Civil Engineering and Architecture, Wuhan University of Technology, No.122 Luoshi Road, Wuhan 430070, China
    Hainan Institute of Wuhan University of Technology, No.5 Chuangxin Road, Yazhou District, Sanya 572024, China)

Abstract

Aiming at the issues of unreasonable cooperation schemes and inappropriate setting of parameters of the refrigeration system with multi-chiller plants, this paper presents a cooperative optimization method to improve the energy performance of the system composed of water-cooled chillers and air-cooled heat pumps. The cooperative optimization process includes scheme optimization and parameter optimization. To content the dynamic cooling load, the working sequence of air-cooled heat pumps and water-cooled chillers with variable frequency chilled water pumps is first optimized. Based on the optimal scheme, a back-propagation neural network (BPNN) coupled with particle swarm optimization (PSO) is implemented to explore the preferred operating parameters of multiple chiller plants corresponding to the best coefficient of performance (COP). Compared with the performance of the initial operation module, the energy consumption of the water pump and fan decreases by over 50%, and the COP of the refrigeration system is improved by 16% (COP = 3.85) through the scheme operation. After parameter optimization, the total energy consumption is reduced by 21.7%, and COP is increased by 26.5% (COP = 4.20). Therefore, the proposed cooperative optimization method can provide useful operation guidance for the refrigeration system with multi-chiller plants.

Suggested Citation

  • Qinli Deng & Liangxin Xu & Tingfang Zhao & Xuexin Hong & Xiaofang Shan & Zhigang Ren, 2022. "Cooperative Optimization of A Refrigeration System with A Water-Cooled Chiller and Air-Cooled Heat Pump by Coupling BPNN and PSO," Energies, MDPI, vol. 15(19), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7077-:d:925927
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    References listed on IDEAS

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    1. Ma, Zhenjun & Wang, Shengwei, 2011. "Supervisory and optimal control of central chiller plants using simplified adaptive models and genetic algorithm," Applied Energy, Elsevier, vol. 88(1), pages 198-211, January.
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    3. 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.
    4. Yu, F.W. & Chan, K.T., 2008. "Optimization of water-cooled chiller system with load-based speed control," Applied Energy, Elsevier, vol. 85(10), pages 931-950, October.
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