Camera-based forecasting of insolation for solar systems

Daniel Manger; Frank Pagel

doi:10.1117/12.2079262

27 February 2015 Camera-based forecasting of insolation for solar systems

Daniel Manger, Frank Pagel

Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 94050M (2015) https://doi.org/10.1117/12.2079262
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

With the transition towards renewable energies, electricity suppliers are faced with huge challenges. Especially the increasing integration of solar power systems into the grid gets more and more complicated because of their dynamic feed-in capacity. To assist the stabilization of the grid, the feed-in capacity of a solar power system within the next hours, minutes and even seconds should be known in advance. In this work, we present a consumer camera-based system for forecasting the feed-in capacity of a solar system for a horizon of 10 seconds. A camera is targeted at the sky and clouds are segmented, detected and tracked. A quantitative prediction of the insolation is performed based on the tracked clouds. Image data as well as truth data for the feed-in capacity was synchronously collected at one Hz using a small solar panel, a resistor and a measuring device. Preliminary results demonstrate both the applicability and the limits of the proposed system.

Citation Download Citation

Daniel Manger and Frank Pagel "Camera-based forecasting of insolation for solar systems", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050M (27 February 2015); https://doi.org/10.1117/12.2079262

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