References

AMT

Atmospheric Measurement Techniques

AMT

Atmos. Meas. Tech.

1867-8548

Copernicus Publications

Göttingen, Germany

10.5194/amt-7-1693-2014

Cloud shadow speed sensor

Fung

¹ Bosch

J. L.

https://orcid.org/0000-0002-8442-0023

¹ Roberts

S. W.

¹ Kleissl

https://orcid.org/0000-0003-4364-0211

Department of Mechanical and Aerospace Engineering, University of California, San Diego, California, USA

12 06 2014

7 6 1693 1700

2014

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://amt.copernicus.org/articles/7/1693/2014/amt-7-1693-2014.html

The full text article is available as a PDF file from https://amt.copernicus.org/articles/7/1693/2014/amt-7-1693-2014.pdf

Changing cloud cover is a major source of solar radiation variability and poses challenges for the integration of solar energy. A compact and economical system is presented that measures cloud shadow motion vectors to estimate power plant ramp rates and provide short-term solar irradiance forecasts. The cloud shadow speed sensor (CSS) is constructed using an array of luminance sensors and a high-speed data acquisition system to resolve the progression of cloud passages across the sensor footprint. An embedded microcontroller acquires the sensor data and uses a cross-correlation algorithm to determine cloud shadow motion vectors. The CSS was validated against an artificial shading test apparatus, an alternative method of cloud motion detection from ground-measured irradiance (linear cloud edge, LCE), and a UC San Diego sky imager (USI). The CSS detected artificial shadow directions and speeds to within 15° and 6% accuracy, respectively. The CSS detected (real) cloud shadow directions and speeds with average weighted root-mean-square difference of 22° and 1.9 m s<sup>−1</sup> when compared to USI and 33° and 1.5 m s<sup>−1</sup> when compared to LCE results.

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