How to manage the forecast error if there is suddenly a thick layer of snow on the solar panels

Numerical weather prediction (NWP) models are the most important time-variant input when forecasting weather-dependent processes, as they cover the upcoming days which are of particular interest in many applications. Selecting the right models, parameters and time periods helps to achieve high forecast accuracy when using machine learning methods with NWP model data.

On October 1, 2021, far-reaching changes for the grid integration of renewable energy sources in Germany will come into force through the new “Redispatch 2.0. As a result, grid operators will be faced with new tasks in which forecasts play an important role.

The Indian Wind Power Association recently published an article by Jonathan Simon, Product Manager at enercast, on the cover story of their eMagazine Windpro “Accurate forecasts for successful renewable energy businesses”.

Each NWP model has certain strengths and weaknesses depending on conditions such as region, terrain type, and forecast horizon. Knowing these strengths and weaknesses allows making well-informed decisions that can assist in producing forecasts with higher accuracy.

Company outing at enercast! After many months working from home, the enercast team finally saw each other in person again. Under the motto “Around the Hirzstein”, the program was a three-hour walk followed by a barbecue.

It is critical to understand the various techniques of measuring accuracy and to carefully identify from the start the ones most suitable for a user’s needs. 

The quality of the input data provided to a state-of-the-art forecasting method for renewable energy is a key factor for forecast accuracy. This input data can be grouped into static data and time-variant data.

A case study on how enercast improves accuracy of our renewable energy forecasts through feedback loop technology is featured in a report recently published by SolarPower Europe, titled ‘Digitalisation & Solar in Emerging Markets’.

Watch enercast co-founder Bernd Kratz explaining the value of big data and how it helps making better decisions, part of the “Digital Germany” tour of impulse magazine.

HA Hessen Agentur has now published a report on the research project Big Energy on their web site.

Smart grids are the future, combining the generation, storage and consumption of electricity. This is essential because, unlike fossil fuels, renewable energies are subject to natural fluctuations.

Saharan dust is not only found in the desert – atmospheric currents carry it over long distances to Central Europe.

enercast offers an additional functionality regarding forecasts for wind turbines – ‘bat shutdown’.

More and more photovoltaic plants are being installed in Europe – 6.9 gigawatts of power were added last year.

Apart from photovoltaics, the renewable energy sector with the strongest growth is wind power.

Data sets of weather models from different meteorological institutes are an important basis for forecasting the performance of wind power and PV systems.

Wind turbines are operated in two ways: Onshore, that means on land, and offshore, i.e. at sea.