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

Abstract

Considering the fact that customers of large commercial buildings have the characteristics of the higher density and randomness, this paper presented an air-conditioning 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.

Keywords

commercial building / load prediction / multiple linear regression

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Acknowledgments

This work was supported by the Key Technology Integration and Demonstration of Green Building Planning and Design for Tianjin Eco-city (No. 2013BAJ09B01).

RIGHTS & PERMISSIONS

2016 Higher Education Press and Springer-Verlag Berlin Heidelberg