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

Author

Listed:
  • Liu, Hua
  • Wu, Zhiyong
  • Zhang, Bingjian
  • Chen, Qinglin
  • Pan, Ming
  • Ren, Jingzheng
  • He, Chang

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.

Suggested Citation

  • Liu, Hua & Wu, Zhiyong & Zhang, Bingjian & Chen, Qinglin & Pan, Ming & Ren, Jingzheng & He, Chang, 2023. "A large-scale stochastic simulation-based thermodynamic optimization for the hybrid closed circuit cooling tower system with parallel computing," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223018285
    DOI: 10.1016/j.energy.2023.128434
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