Cluster Partition Operation Study of Air-Cooled Fan Groups in a Natural Wind Disturbance

Guijie Zheng, Wentao Wen, Hui Deng () and Yang Cai ()
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Guijie Zheng: Energy and Electricity Research Centre, Jinan University, Zhuhai 519070, China
Wentao Wen: Energy and Electricity Research Centre, Jinan University, Zhuhai 519070, China
Hui Deng: Energy and Electricity Research Centre, Jinan University, Zhuhai 519070, China
Yang Cai: Energy and Electricity Research Centre, Jinan University, Zhuhai 519070, China

Energies, 2023, vol. 16, issue 9, 1-20

Abstract: This study discusses the influence of natural wind on the air flow of air-cooled condensers (ACCs) and then proposes a partition speed-regulation strategy for a fan group with enhanced generalized capability, which is of great practical significance for optimizing energy-saving operations. The stochastic time-varying features of natural wind are characterized by sine–Gaussian, Weibull, and composed winds. In a natural wind disturbance, using the Sugon Supercomputing Center, the transient numerical simulation of the dynamic evolution of the ACC flow field was found: the dynamic system of air flow is a typical time-varying nonlinear process. Cluster analysis was used to extract the nonlinear features of air flow, divide the fan group into four subregions with generalization capability, and implement a partitioned speed operation. It was found that giving priority to increasing the fan speed in the headwind partition can suppress the natural wind disturbance and improve the overall air flow, thus reducing the fan speed in the leeward partition, which reduces the overall air flow loss. The dynamic characteristics of the fan group obtained from the simulation and the proposed fan partition method can guide the optimized energy-saving operation of ACCs.

Keywords: air-cooled condenser; fan group; cluster analysis; transient numerical simulation; natural wind speed model; partition strategy; speed regulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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