水源CO_2热泵的全工况性能与匹配性分析

Performance and match analysis of water-source CO_2 heat pump under full-range operating conditions

通过对60kW水源CO_2热泵的实验测试,在获得的911组实验数据的基础上,建立了用于反映热泵系统性能和循环参数随运行工况变化趋势的BP神经网络拟合模型,综合分析了系统在供水温度为55~100℃、回水温度为10~50℃、热源温度为5~50℃和电子膨胀阀开度为50~400步的全工况范围内的性能,从而为该类型热泵系统性能的预测和系统设计提供了数据参考。在对四种工况下,即15/55/15℃、15/90/15℃、15/90/30℃和30/90/30℃时系统运行参数的比较分析的基础上,定性评价了系统在全工况范围内的匹配性。

Based on the 911 data points obtained from the experimental test on the 60 kW water-source heat pump, a back propagation （BP） neural network fitting model was set up, which can be used to describe the variation of system performance and cycle parameters with operating conditions. With the aid of this model, the system performance under full-range operating conditions （hot water temperature varied within 55-100 ℃, return water temperature within 10-50 ℃, heat source water temperature 5-50 ℃ and open degree of electronic expansion valve within 50-400） were systematically analyzed, and this can thus be useful for predicting system performance and for design of such heat pump system. Based on comparative analysis of the operating parameters of the heat pump system under operating conditions 15/55/15 ℃, 15/90/15 ℃, 15/90/30 ℃ and 30/90/30 ℃, the system match under full-range operating conditions was qualitatively judged.