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.

Highlights

  • The power supply system is under fundamental transition

  • We calculated the absolute difference of the optical flow estimate and the measured satellite image as described in Section 2.3 to decide whether the Farnebäck or the total variation (TV)-L1 method performed better for the effective cloud albedo

  • The TV-L1 method shows better results for all examined cases, so that this method is used to estimate the optical flow with the effective cloud albedo

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Summary

Introduction

The power supply system is under fundamental transition. The replacement of fossil fuels by renewable energy is progressing rapidly. The integration of wind and solar energy into the grid has a huge impact on the load flows. For this reason, the forecasts of solar radiation and wind have to be more precise with particular regard to the short-term forecast for up to 3–4 h. A forecast based on satellite observations, referred to as nowcasting, is of priority choice for this issue. It shows better results for the first few hours of photovoltaic power forecasts (PV forecasts) in comparison to numerical weather prediction models (NWP) [1]. The results of the numerical weather prediction model are only available with a time delay of several hours, whereas satellite-based forecasts are available in near real time

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