Application of system identification modelling to solar hybrid systems for predicting radiation, temperature and load

被引:4
|
作者
Sinha, S
Kumar, S
Matsumoto, T
Kojima, T
机构
[1] Seikei Univ, Fac Engn, Dept Ind Chem, Tokyo 1808633, Japan
[2] Kyoto Univ, Dept Global Environm Eng, Sakyo Ku, Kyoto 60601, Japan
关键词
Mathematical models - Parameter estimation - Regression analysis - Solar radiation - Temperature - Thermal load;
D O I
10.1016/S0960-1481(00)00034-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Uncertainties in local solar radiation, ambient temperature and thermal load data have been one of the major factors limiting the reliability and efficiency of solar thermal hybrid systems. In the present paper, moving average auto regressive exogenous (ARX) model based reasoning has been mooted and modified to include moving average method, as an effective tool for predictions of these data. The results show that the method is quite robust and is capable of predicting fairly accurate results, which would make these systems more viable in areas where meteorological data are not available or vague. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:281 / 286
页数:6
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