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针对冷却水塔的节能操作给出了一种数据驱动的建模与优化方法。首先,基于冷却水塔实际运行数据,应用非负绞杀变量选择方法给出一个自适应模型用于描述冷却水塔过程,该模型对于冷却水塔出口水温具有良好的预测精度。根据变量选择结果,分析了外界空气温度与湿度对冷却能力的影响。然后,提出了基于模型的冷却水塔风机的优化操作策略,并进行实验将之应用于冷却水塔的操作。研究结果显示,基于模型的优化操作具有较大的节能空间。
A data-driven modeling and optimization approach is presented for the energy-saving operation of cooling towers. First of all, based on the actual operating data of cooling towers, an adaptive model is proposed to describe the process of cooling tower with non-negative strangulation variables. The model has good prediction accuracy for the outlet water temperature of cooling towers. According to the results of variable selection, the influence of outside air temperature and humidity on cooling capacity is analyzed. Then, the optimal operating strategy of the model-based cooling tower blower is put forward and applied to the operation of the cooling tower. The results show that the optimization based on the model has more energy-saving space.