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

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  • 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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    References listed on IDEAS

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    1. Li, Wuyan & Li, Yongcai & Shi, Wenxing & Lu, Jun, 2021. "Energy and exergy study on indirect evaporative cooler used in exhaust air heat recovery," Energy, Elsevier, vol. 235(C).
    2. Qu, Jinghui & Li, Mingjian & He, Chang & Zhang, BingJian & Chen, QingLin & Ren, Jingzheng, 2022. "Deciphering the optimal exergy field in closed-wet cooling towers using Bi-level reduced-order models," Energy, Elsevier, vol. 238(PA).
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    4. Wu, Zhiyong & Lu, Zhibin & Zhang, Bingjian & He, Chang & Chen, Qinglin & Yu, Haoshui & Ren, Jingzheng, 2022. "Stochastic bi-objective optimization for closed wet cooling tower systems based on a simplified analytical model," Energy, Elsevier, vol. 250(C).
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    1. You-Shyang Chen & Ying-Hsun Hung & Mike Yau-Jung Lee & Jieh-Ren Chang & Chien-Ku Lin & Tai-Wen Wang, 2024. "Advanced Study: Improving the Quality of Cooling Water Towers’ Conductivity Using a Fuzzy PID Control Model," Mathematics, MDPI, vol. 12(20), pages 1-27, October.

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