Abstract
The cloud index is a key parameter of the Heliosat method. This method is widely used to calculate solar irradiance on the Earth’s surface from Meteosat visible channel images. Moreover, cloud index images are the basis of short-term forecasting of solar irradiance and photovoltaic power production. For this purpose, cloud motion vectors are derived from consecutive images, and the motion of clouds is extrapolated to obtain forecasted cloud index images. The cloud index calculation is restricted to the daylight hours, as long as SEVIRI HR-VIS images are used. Hence, this forecast method cannot be used before sunrise. In this paper, a method is introduced that can be utilized a few hours before sunrise. The cloud information is gained from the brightness temperature difference (BTD) of the 10.8 µm and 3.9 µm SEVIRI infrared channels. A statistical relation is developed to assign a cloud index value to either the BTD or the brightness temperature T10:8, depending on the cloud class to which the pixel belongs (fog and low stratus, clouds with temperatures less than 232 K, other clouds). Images are composed of regular HR-VIS cloud index values that are used to the east of the terminator and of nighttime BTD-derived cloud index values used to the west of the terminator, where the Sun has not yet risen. The motion vector algorithm is applied to the images and delivers a forecast of irradiance at sunrise and in the morning. The forecasted irradiance is validated with ground measurements of global horizontal irradiance, and the advantage of the new approach is shown. The RMSE of forecasted irradiance based on the presented nighttime cloud index for the morning hours is between 3 and 70 W/m2, depending on the time of day. This is an improvement against the previous precision range of the forecast based on the daytime cloud index between 70 and 85 W/m2.
Highlights
With the steadily increasing contribution of photovoltaic (PV) power to the electricity mix in Europe and especially in Germany, reliable predictions of the expected PV power production are becoming increasingly important as a basis for power and grid management and operation strategies
The approach presented in this paper offers a continuous cloud product and is inspired by Mosher’s approach to use brightness temperature difference (BTD) values for fog and low stratus and brightness temperature values T10.8 for other clouds
The spread of the forecasts based on cloud index, including Rozenberg airmass, is significantly reduced compared to forecasts for the same situations using the cloud index values based on Equation (2) with unlimited airmass
Summary
With the steadily increasing contribution of photovoltaic (PV) power to the electricity mix in Europe and especially in Germany, reliable predictions of the expected PV power production are becoming increasingly important as a basis for power and grid management and operation strategies. For the operational detection of high semi-transparent clouds or low water clouds, brightness temperature thresholds are pre-calculated with radiative transfer calculations for variable water vapor content and different satellite viewing angles. The brightness temperature difference varies with the length of the slant atmospheric column between sensor and object (limb cooling) and the varying concentrations of CO2 To account for these effects, the authors have presented a dynamic extraction of BTD thresholds for different satellite viewing angles. The approach presented in this paper offers a continuous cloud product and is inspired by Mosher’s approach to use BTD values for fog and low stratus and brightness temperature values T10.8 for other clouds. The satellite viewing angle is accounted for to avoid the limb cooling observed in SEVIRI BTD This enables the use of uniform thresholds within the European image section when assigning clouds to these three classes. The main focus of the validation is to study if the introduction of the nighttime cloud index improves the forecasting of surface solar irradiance
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