Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34093
Title: A grey-box model of next-day building thermal load prediction for energy-efficient control
Authors: Zhou, Q
Wang, S 
Xu, X
Xiao, F 
Keywords: Building load
Grey-box model
Load prediction
Weather prediction
Issue Date: 2008
Source: International journal of energy research, 2008, v. 32, no. 15, p. 1418-1431 How to cite?
Journal: International Journal of Energy Research 
Abstract: Accurate building thermal load prediction is essential to many building energy control strategies. To get reliable prediction of the hourly building load of the next day, air temperature/relative humidity and solar radiation prediction modules are integrated with a grey-box model. The regressive solar radiation module predicts the solar radiation using the forecasted cloud amount, sky condition and extreme temperatures from on-line weather stations, while the forecasted sky condition is used to correct the cloud amount forecast. The temperature/relative humidity prediction module uses a dynamic grey model (GM), which is specialized in the grey system with incomplete information. Both weather prediction modules are integrated into a building thermal load model for the on-line prediction of the building thermal load in the next day. The validation of both weather prediction modules and the on-line building thermal load prediction model are presented.
URI: http://hdl.handle.net/10397/34093
ISSN: 0363-907X
DOI: 10.1002/er.1458
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