期刊
CHINESE JOURNAL OF CHEMICAL ENGINEERING
卷 58, 期 -, 页码 244-255出版社
CHEMICAL INDUSTRY PRESS CO LTD
DOI: 10.1016/j.cjche.2022.10.021
关键词
Optimal design; Process systems; Particle Swarm Optimization; Simulated annealing; Mathematical modeling
This study presented a stochastic optimization method for the synthesis of cascade refrigeration system (CRS) with simultaneous consideration of heat integration between refrigerant and process streams. The proposed methodology was verified by a case study of CRS optimization in an ethylene plant, achieving 21.89% the total annual cost saving.
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 sav-ing and reduction of carbon emission. This study presented a stochastic optimization method for the syn-thesis 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 optimiza-tion 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.(c) 2022 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights reserved.
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