A large-scale stochastic simulation-based thermodynamic optimization for the hybrid closed circuit cooling tower system with parallel computing

Hua Liu, Zhiyong Wu, Bingjian Zhang, Qinglin Chen, Ming Pan, Jingzheng Ren and Chang He

Energy, 2023, vol. 283, issue C

Abstract: The emerging multi-mode cooling tower can cool down the circulating water by flexibly switching the operating modes according to varying weather conditions. Herein, a computational framework for addressing a large-scale stochastic simulation-optimization task is developed to obtain the optimal thermodynamic performance of the multi-mode cooling system. First, the numerical model is constructed using a well-validated evaporative cooler in the wet and wet-heating modes, as well as an air cooler in the dry mode. A well-suited experimental design is performed for generating an optimal set of samples by approximating the multivariate probability distributions of uncertain data. To reduce the computational burden, a customized parallel computing strategy is presented via parallelization of the task using the message-passing interface. Finally, an example illustrates that the time reduction is up to 93.5%, while the optimal exergy efficiency ratios are expected to be 37.0%, 17.3%, and 22.6% for the wet, dry, and wet-heating modes, respectively.

Keywords: Multi-mode cooling tower; Thermodynamic performance; Stochastic simulation-optimization; Parallel computing; Message-passing interface; Exergy efficiency ratio (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:283:y:2023:i:c:s0360544223018285

DOI: 10.1016/j.energy.2023.128434

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