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A Novel Approach for the Short-Term Forecast of the Effective Cloud Albedo

1
Faculty of Geography, Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
2
Philipps-Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 955; https://doi.org/10.3390/rs10060955
Received: 27 April 2018 / Revised: 23 May 2018 / Accepted: 8 June 2018 / Published: 15 June 2018
(This article belongs to the Section Atmosphere Remote Sensing)
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Abstract

The increasing use of renewable energies as a source of electricity has led to a fundamental transition of the power supply system. The integration of fluctuating weather-dependent energy sources into the grid already has a major impact on its load flows. As a result, the interest in forecasting wind and solar radiation with a sufficient accuracy over short time periods (<4 h) has grown. In this study, the short-term forecast of the effective cloud albedo based on optical flow estimation methods is investigated. The optical flow method utilized here is TV-L1 from the open source library OpenCV. This method uses a multi-scale approach to capture cloud motions on various spatial scales. After the clouds are displaced, the solar surface radiation will be calculated with SPECMAGIC NOW, which computes the global irradiation spectrally resolved from satellite imagery. Due to the high temporal and spatial resolution of satellite measurements, the effective cloud albedo and thus solar radiation can be forecasted from 5 min up to 4 h with a resolution of 0.05°. The validation results of this method are very promising, and the RMSE of the 30-min, 60-min, 90-min and 120-min forecast equals 10.47%, 14.28%, 16.87% and 18.83%, respectively. The paper gives a brief description of the method for the short-term forecast of the effective cloud albedo. Subsequently, evaluation results will be presented and discussed. View Full-Text
Keywords: effective cloud albedo; solar surface irradiance; optical flow; cloud motion vectors; renewable energies effective cloud albedo; solar surface irradiance; optical flow; cloud motion vectors; renewable energies
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Urbich, I.; Bendix, J.; Müller, R. A Novel Approach for the Short-Term Forecast of the Effective Cloud Albedo. Remote Sens. 2018, 10, 955.

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