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Chapitre D'ouvrage Année : 2017

Solar Power Forecasting Based on Sky Cameras

Résumé

Solar resource and forecasting in very short spatial and timescales (0–100 m, 0–30 min) is a challenging task that cannot be accurately achieved by satellite products or numerical weather predictions due to technical and methodological restrictions. For this reason, sky images from ground-based cameras are widely used during the last decade to deal with the high spatial and temporal variability of clouds and provide the needed inputs for numerical models for the current and forecasted (in short-term) solar irradiance. In this chapter, the available types of all-sky cameras/imagers are shortly presented. The chapter is focused on the state-of-the-art methodologies used to derive parameters needed for the estimations of solar resource and forecasting by a calibrated all-sky camera: cloud coverage, type, height, and velocity as well as aerosol optical properties. The application of these methodologies at Plataforma Solar de Almeria, in the frame of project: “Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies” (DNICast, http://www.dnicast-project.net/) is discussed. Finally, the chapter finishes with some propositions for future work in the recent, but quickly, developed research area.
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Dates et versions

hal-01542848 , version 1 (20-06-2017)

Identifiants

Citer

Andreas Kazantzidis, Panagiotis Tzoumanikas, Philippe Blanc, Pierre Massip, Stefan Wilbert, et al.. Solar Power Forecasting Based on Sky Cameras. Renewable Energy Forecasting: From Models to Applications , Elsevier - Woodhead Publishing, Chapter 5 - p. 153-178, 2017, Woodhead Publishing Series in Energy, 978-0-0810-0504-0 ⟨10.1016/B978-0-08-100504-0.00005-6⟩. ⟨hal-01542848⟩
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