Application of heuristic algorithms for design optimization of industrial heat pump. (February 2022)

• Record Type: Journal Article
• Authors: Oh, Bong Seong; Cho, Junhyun; Choi, Bongsu; Choi, Hong Wone; Kim, Min Soo; Lee, Gilbong
• Is Part Of: International journal of refrigeration. Volume 134(2022)
• Page Start: 1
• Page End: 15
• Publication Date: 2022-02
• Subjects: Industrial heat pump -- Heat pump cycle optimization -- Next-generation refrigerants -- Genetic algorithm -- Particle swarm optimization -- Simulated annealing; Pompe à chaleur industrielle -- Optimisation du cycle d'une pompe à chaleur -- Frigorigènes de future génération -- Algorithme génétique -- Optimisation par essaims particulaires -- Recuit simulé; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2021.11.002
• Languages: English
• ISSNs: 0140-7007

Abstract

Abstract: The design parameters of heat pumps are related to each other nonlinearly or in a complicated manner; therefore, it is difficult to determine the optimal combination of design parameters, such as superheat, subcooling, and refrigerant type, analytically. To address this limitation, three representative heuristic algorithms, namely the genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA), are applied to optimize a heat pump under the given process conditions. Heuristic algorithms are driven based on randomness; thus, the consistency of the calculation results and computational time represent the decision criteria for the appropriate optimizer. The GA is unsuitable as a heat pump optimizer because it requires an excessive number of iterations. In contrast, PSO and SA have a similar capability of consistency and calculation time with a rational number of iterations. In conclusion, PSO exhibits a slightly better consistency and use of computational resources; therefore, PSO is selected as the heat pump design optimization algorithm in this study. The novelty of this work lies in that the related design parameters of the heat pump are simultaneously globally optimized with minimal physical background, and the heuristic algorithm that is most applicable to heat pump design optimization is determined.