A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

作者：Jia, Junbao; Xing, Jincheng; Ling, Jihong^*; Peng, Ren

来源：Frontiers in Energy, 2016, 10(4): 459-465.

DOI：10.1007/s11708-016-0424-8

• commercial building
• load prediction
• multiple linear regression

Considering the fact that customers of large commercial buildings have the characteristics of the higher density and randomness, this paper presented an airconditioning cooling load prediction method based on weather forecast and internal occupancy density. The multiple linear feedback regression model was applied to predict, with precision, the air conditioning cooling load. Case analysis showed that the largest mean relative error of hourly and the daily predicting cooling load maximum were 18.1% and 5.14%, respectively.

• 出版日期2016-12
• 单位天津大学