Sky-Imaging Systems for Short-Term Forecasting

Urquhart, B.; Ghonima, M. S.; Nguyen, Dung; Kurtz, Ben; Chow, C. W.; Kleissl, Jan

doi:10.1016/b978-0-12-397177-7.00009-7

Cited by 42 publications

(42 citation statements)

References 32 publications

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“…Currently several different methods are used to forecast at different spatial and temporal resolutions including numerical weather prediction (e.g., Lorenz et al, 2009;Mathiesen and Kleissl, 2011) and satellite imagebased forecasting (e.g., Hammer et al, 1999). For short-term forecasting, whole-sky imagery has been used (e.g., Urquhart et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

et al. 2016

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Abstract. A method for retrieving cloud optical depth (τ c ) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red-blue ratio (RRBR) method is motivated from the analysis of simulated images of various τ c produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red-blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ 0 ), τ c , solar pixel angle/scattering angle (ϑ s ), and pixel zenith angle/view angle (ϑ z ). The effects of these parameters are described and the functions for radiance, I λ (τ c , θ 0 , ϑ s , ϑ z ), and RBR(τ c , θ 0 , ϑ s , ϑ z ) are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τ c , where RBR increases with τ c up to about τ c = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured I meas λ (ϑ s , ϑ z ), in addition to RBR meas (ϑ s , ϑ z ), to obtain a unique solution for τ c . The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003)

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Section: Introductionmentioning

confidence: 99%

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

et al. 2016

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“…The University of California, San Diego (UCSD) sky imager (USI) camera system was developed for the purpose of solar power forecasting (Urquhart et al, 2013 Figure 1 shows the USI on its portable mounting stand.…”

Section: Imaging Equipment and Setupmentioning

confidence: 99%

“…Specifically for solar power forecasting, a number of technologies are being applied: numerical weather prediction (e.g., Lorenz et al, 2009;Mathiesen and Kleissl, 2011;; satellite image-based forecasting (e.g., Hammer et al, 1999;Perez and Hoff, 2013); and stochastic learning methods (e.g., Bacher et al, 2009;Marquez and Coimbra, 2011;Pedro and Coimbra, 2012). For very short term (15 min ahead) solar power forecasting on the kilometer scale, sky imaging from ground stations has demonstrated utility (Chow et al, 2011;Urquhart et al, 2013;Marquez and Coimbra, 2013;Yang et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Sky camera geometric calibration using solar observations

2016

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Abstract. A camera model and associated automated calibration procedure for stationary daytime sky imaging cameras is presented. The specific modeling and calibration needs are motivated by remotely deployed cameras used to forecast solar power production where cameras point skyward and use 180 • fisheye lenses. Sun position in the sky and on the image plane provides a simple and automated approach to calibration; special equipment or calibration patterns are not required. Sun position in the sky is modeled using a solar position algorithm (requiring latitude, longitude, altitude and time as inputs). Sun position on the image plane is detected using a simple image processing algorithm. The performance evaluation focuses on the calibration of a camera employing a fisheye lens with an equisolid angle projection, but the camera model is general enough to treat most fixed focal length, central, dioptric camera systems with a photo objective lens. Calibration errors scale with the noise level of the sun position measurement in the image plane, but the calibration is robust across a large range of noise in the sun position. Calibration performance on clear days ranged from 0.94 to 1.24 pixels root mean square error.

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“…One short-term forecasting technology that has emerged recently has been based on remote sensing of clouds from ground-based imaging systems (Chow et al, 2011;Marquez and Coimbra, 2013;Urquhart et al, 2013;Yang et al, 2014;Fu and Cheng, 2013). Urquhart et al (2013) applied the forecasting method to 48MW of photovoltaic generation.…”

Section: Introductionmentioning

confidence: 99%

“…Urquhart et al (2013) applied the forecasting method to 48MW of photovoltaic generation. One of the key conclusions from that work was that the Total Sky Imager (TSI), while providing the ability to monitor sky conditions, had shortcomings that limit its effectiveness for solar power forecasting.…”

Section: Introductionmentioning

confidence: 99%

Development of a sky imaging system for short-term solar power forecasting

et al. 2015

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Abstract.To facilitate the development of solar power forecasting algorithms based on ground-based visible wavelength remote sensing, we have developed a high dynamic range (HDR) camera system capable of providing hemispherical sky imagery from the circumsolar region to the horizon at a high spatial, temporal, and radiometric resolution. The University of California, San Diego Sky Imager (USI) captures multispectral, 16 bit, HDR images as fast as every 1.3 s. This article discusses the system design and operation in detail, provides a characterization of the system dark response and photoresponse linearity, and presents a method to evaluate noise in high dynamic range imagery. The system is shown to have a radiometrically linear response to within 5 % in a designated operating region of the sensor. Noise for HDR imagery is shown to be very close to the fundamental shot noise limit. The complication of directly imaging the sun and the impact on solar power forecasting is also discussed. The USI has performed reliably in a hot, dry environment, a tropical coastal location, several temperate coastal locations, and in the great plains of the United States.

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Sky-Imaging Systems for Short-Term Forecasting

Cited by 42 publications

References 32 publications

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

Sky camera geometric calibration using solar observations

Development of a sky imaging system for short-term solar power forecasting

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