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Cloud shadow speed sensor
DOI:10.5194/amt-7-1693-2014.png)
Abstract
En 中文
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 degrees and 6% accuracy, respectively. The CSS detected (real) cloud shadow directions and speeds with average weighted root-mean-square difference of 22 degrees and 1.9 ms(-1) when compared to USI and 33 degrees and 1.5 ms(-1) when compared to LCE results.
Keywords:
SOLAR-RADIATION
SKY IMAGER
Journal
IF:
3.3
Papers:
5.4K
Citations:
1.8W
Organization
Cited Papers
Short-term forecasting of solar radiation:: A statistical approach using satellite data
SOLAR ENERGY
IF6.6
Cloud speed impact on solar variability scaling - Application to the wavelet variability model
SOLAR ENERGY
IF6.6
Validation of short and medium term operational solar radiation forecasts in the US
SOLAR ENERGY
IF6.6
Solar irradiance forecasting using a ground-based sky imager developed at UC San Diego
SOLAR ENERGY
IF6.6
Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed
SOLAR ENERGY
IF6.6

