Articles | Volume 16, issue 5
Research article
15 Mar 2016
Research article |  | 15 Mar 2016

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

Thomas Schmidt, John Kalisch, Elke Lorenz, and Detlev Heinemann

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Cited articles

Bernecker, D., Riess, C., Angelopoulou, E., and Hornegger, J.: Continuous short-term irradiance forecasts using sky images, Sol. Energy, 110, 303–315,, 2014.
Blanc, P. and Wald, L.: A Library for Computing the Relative Position of the Sun and the Earth, Tech. rep., GMES, Paris, France, 2011.
Bouguet, J.-Y.: Pyramidal implementation of the affine lucas kanade feature tracker description of the algorithm, Intel Corporation, 5, 1–10, 2001.
Bourges, B. D.: Yearly variations of the Linke turbidity factor, in: Climatic Data Handbook of Europe, Kluwer Academic Publishing, Dordrecht, the Netherlands, 61–64, 1992.
Cazorla, A.: Development of a Sky Imager for Cloud Classification and Aerosol Characterization, PhD thesis, Universidad de Granada, Granada, Spain, 2010.
Short summary
We performed an irradiance forecast experiment based on analysis of hemispheric sky images and evaluated results on a large data set of 99 pyranometers distributed over 10 × 12 km. We developed a surface irradiance retrieval from cloud information derived from the images. Very high resolution forecasts were processed up to 25 min. A main finding is that forecast skill is enhanced in complex cloud conditions leading to high variability in surface irradiance.
Final-revised paper