准确的冷负荷预测能减低空调能耗,对建筑节能意义重大。针对回归方法不能实时反映外部因素突变问题,提出一种实时气象因子和历史负荷为输入变量的自回归模型(ARX模型)的冷负荷预测方法。对辐射的情况进行分类,用最小二乘法辨识模型的参数,并与De ST仿真结果进行比较。实验结果表明:该方法可实现对冷负荷的逐时预测,具有良好的准确性,且简单有效。 Accurate cooling load forecasting can reduce the energy consumption of air conditioning, which is of great significance to building energy saving. Aiming at the problem that the regression method can not reflect the sudden change of external factors in real time, a method of cold load forecasting based on real-time meteorological factors and ARX model with historical load as input variables is proposed. The radiation conditions were classified, the parameters of the model were identified by least square method, and compared with De ST simulation results. The experimental results show that this method can realize the hourly prediction of cooling load with good accuracy and is simple and effective.