SCI和EI收录∣中国化工学会会刊

Chinese Journal of Chemical Engineering ›› 2023, Vol. 58 ›› Issue (6): 244-255.DOI: 10.1016/j.cjche.2022.10.021

Previous Articles     Next Articles

Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm

Danlei Chen1, Yiqing Luo1, Xigang Yuan1,2   

  1. 1. Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China;
    2. State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300350, China
  • Received:2022-09-04 Revised:2022-10-26 Online:2023-08-31 Published:2023-06-28
  • Contact: Yiqing Luo,E-mail:luoyq@tju.edu.cn;Xigang Yuan,E-mail:yuanxg@tju.edu.cn
  • Supported by:
    This research was supported by the National Natural Science Foundation of China (21978203) and the Natural Science Foundation of Tianjin City (19JCYBJC20300).

Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm

Danlei Chen1, Yiqing Luo1, Xigang Yuan1,2   

  1. 1. Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China;
    2. State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300350, China
  • 通讯作者: Yiqing Luo,E-mail:luoyq@tju.edu.cn;Xigang Yuan,E-mail:yuanxg@tju.edu.cn
  • 基金资助:
    This research was supported by the National Natural Science Foundation of China (21978203) and the Natural Science Foundation of Tianjin City (19JCYBJC20300).

Abstract: Cascade refrigeration system (CRS) can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system, making it more widely used in low-temperature industry processes. The synthesis of a CRS with simultaneous consideration of heat integration between refrigerant and process streams is challenging but promising for significant cost saving and reduction of carbon emission. This study presented a stochastic optimization method for the synthesis of CRS. An MINLP model was formulated based on the superstructure developed for the CRS, and an optimization framework was proposed, where simulated annealing algorithm was used to evolve the numbers of pressure/temperature levels for all sub-refrigeration systems, and particle swarm optimization algorithm was employed to optimize the continuous variables. The effectiveness of the proposed methodology was verified by a case study of CRS optimization in an ethylene plant with 21.89% the total annual cost saving.

Key words: Optimal design, Process systems, Particle swarm optimization, Simulated annealing, Mathematical modeling

摘要: Cascade refrigeration system (CRS) can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system, making it more widely used in low-temperature industry processes. The synthesis of a CRS with simultaneous consideration of heat integration between refrigerant and process streams is challenging but promising for significant cost saving and reduction of carbon emission. This study presented a stochastic optimization method for the synthesis of CRS. An MINLP model was formulated based on the superstructure developed for the CRS, and an optimization framework was proposed, where simulated annealing algorithm was used to evolve the numbers of pressure/temperature levels for all sub-refrigeration systems, and particle swarm optimization algorithm was employed to optimize the continuous variables. The effectiveness of the proposed methodology was verified by a case study of CRS optimization in an ethylene plant with 21.89% the total annual cost saving.

关键词: Optimal design, Process systems, Particle swarm optimization, Simulated annealing, Mathematical modeling