制冷与空调

为了降低数据中心的能耗和碳排放水平，文章针对河北省某数据中心，建立了模块化机房内间接蒸发冷却系统模型，并对其进行了验证。结果表明，试验空气出口温度与模拟数据之间的最大误差为4.51%。文章通过模拟进一步分析了4个运行参数对系统性能的影响。结果表明，当新回风比从0.8增加到0.9时，系统耗电量和耗水量分别增加了29.81%和12.5%。而当喷淋功率从90%增加到98%时，它们分别增加了25.33%和8.89%。同时，通过参数优化，提出了不同负荷率下蒸发冷却系统的最佳调控方法。当实际负荷率为0.5和0.6时，蒸发冷却系统的最佳送风流量、新回风比和喷淋功率分别为9.0×10⁴ kg/h、0.8和90%。当实际负荷率为0.7时，建议针对数据中心所在当地的水资源和能源价格情况，通过增加喷淋功率或送风流量来调控模块机房的室内温度。上述研究将为数据中心模块机房内蒸发冷却系统的性能优化和运行控制提供理论指导。

In order to reduce the energy consumption and carbon emissions of data centers, a model is established and validated for the indoor evaporative cooling system in a module room based on a data center in Hebei. The results show that the maximum error is 4.51% between the experimental outlet supply air temperature and simulated data. Further, the effect of four operating parameters is analyzed for system performance through simulation. The results show that when the new-return air ratio increases from 0.8 to 0.9, the power and water consumption of system increase by 77.15% and 12.5%, res-pectively. However, when the spray power increases from 90% to 98%, they increase by 25.33% and 8.89%, respectively. Finally, the optimal control method is proposed for the evaporative cooling system under different load rates through parameter optimization. When the actual load rates are 0.5 and 0.6, the optimal supply air flow rate, new-return air ratio and spray power are 9.0×10⁴ kg/h, 0.8 and 90%, respectively. When the actual load rate is 0.7, it is recommended to regulate the indoor temperature by increasing the spray power or supply air flow rate based on local water resources and energy prices. The above research will provide theoretical guidance for the performance optimization and operating control ofevaporative cooling systems in data centers.