Optimal Interpolation of Satellite Derived Irradiance and Ground Data

被引：0

作者：

Lorenzo, Antonio T. ^{[1
]}

Morzfeld, Matthias ^{[2
]}

Holmgren, William F. ^{[3
]}

Cronin, Alexander D. ^{[4
]}

机构：

[1] Univ Arizona, Coll Opt Sci, Tucson, AZ 85721 USA

[2] Univ Arizona, Dept Math, Tucson, AZ 85721 USA

[3] Univ Arizona, Dept Atmospher Sci, Tucson, AZ 85721 USA

[4] Univ Arizona, Dept Phys, Tucson, AZ 85721 USA

来源：

2016 IEEE 43RD PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC) | 2016年

关键词：

data assimilation; optimal interpolation; remote sensing; solar irradiance; MODEL;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GHI) using ground truth data that was collected sparsely over Tucson, AZ. Our results show that the local data indeed improves the satellite derived estimates of GHI. A key to success with OI in this context is to prescribe correlations based on cloudiness, rather than spatially. OI can be used with a variety of data, e.g., rooftop photovoltaic production data or irradiance data, as well as with several different satellite derived irradiance models.

引用

页码：291 / 296

页数：6

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