Leistungsprognosen Wind und Solar


Improved solar power forecasts by means of optimised snow detection:

Although there may be sunny weather now, this will certainly be followed by another winter which will bring snow to some regions. Forecasters are facing the challenge of how to take into account snow coverage and snow slippage in their solar power forecasts. enercast has now introduced two models into its forecasting  system that take optimum account of these weather conditions.

Snow-covered photovoltaic plants do not produce a significant amount of electricity, even if the sky is clear. What is even more problematic for grid operators and energy traders is the question of when these plants will once again be able to produce electricity.

Due to the angle of inclination of photovoltaic panels, snow could slide down the panel at any time, or it could partially melt. This would lead to significant fluctuations in a large proportion of solar plants in the grid or in the portfolio.

Difficult weather conditions in the area of solar power forecasts:

In order to improve PV power forecasts, enercast has extended its portfolio to include data sources for difficult weather conditions.  For this purpose, enercast has integrated data from both the NSIDC’s “IMS Daily Northern Hemisphere Snow and Ice Analysis” model and EUMETSAT’s “Land Surface Analysis Satellite Applications Facility (LSA SAF)”.

Following the integration of this data, the expected snow load and the reduction in output due to snow cover can be calculated more accurately by the artificial neural network. The result is an optimised solar power forecast in the event of the extreme weather situation – “Snow”.

Further information on satellite models:

NSIDC IMS Daily Northern Hemisphere Snow and Ice Analysis

(Source: National Snow and Ice Data Center)

Seen from the North Pole, the Earth looks somewhat unusual. But certain geographical shapes like Europe are clearly identifiable. This satellite model supports enercast by providing data on snow and ice formation. It is based on a wide range of measurement data and numerical weather modelling data.



(Source: copyright 2017 EUMETSAT)

This model uses EUMETSAT satellites, e.g. Meteosat satellites. These satellites are located  in geostationary orbit approx. 36,000 km from Earth and continuously transmit various measurement data.

enercast is supplied with a range of parameters, including for example measured solar radiation. This helps enercast to further improve its extrapolations and PV power forecasts. Alongside information on snow coverage, which is processed in real time, the model also supplies important information regarding potential losses in output.

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enercast GmbH allows the integration of wind and solar energy into electricity grids and energy markets by precisely predicting their energy output.