Cloud speed sensor

Abstract

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 that measures cloud motion vectors to estimate power plant ramp rates and provide short term solar irradiance forecasts is presented. The Cloud Speed Sensor (CSS) is constructed 5 using an array of luminance sensors and high-speed data acquisition to resolve the progression of cloud passages across the sensor footprint. An embedded microcon-troller acquires the sensor data and uses a cross-correlation algorithm to determine cloud motion vectors. The CSS was validated against an artificial shading test apparatus , an alternative method of cloud motion detection from ground measured irradiance 10 (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 directions and speeds without average bias and with average weighted root mean square difference of 22 • and 1.9 m s −1 when compared to USI and 33 • and 1.5 m s −1 when compared to LCE results. 15