We use a self-learning algorithm to produce power and yield forecasts for wind energy and photovoltaic plants, giving you a realistic idea of how much energy your wind or solar park will produce on a particular day (intraday), the following day (day-ahead), or over a longer period (long-term). We offer these forecasts as part of customized service packages that are tailored to your needs.
Preparing wind assessment reports can be complex and time-consuming, usually taking several months. Our digital wind assessment (DWA) takes a fraction of the time by digitalizing layout checks and data analyses, creating a wind model, and providing other beneficial features. The DWA structures tasks from start to finish and collects the data in a central location. This digitalized solution saves you time because it enables you to submit funding application documents more quickly.
Our future-oriented and individually configurable service modules allow us to specifically cater to your requirements. We select the right forecast module based on the data available. The forecast modules can also be complemented by our optimization modules.
As part of the EU-funded MAELSTROM project, 4cast has been passionately and consistently driving innovations in machine learning and high-performance computing with a focus on processing weather data. Generating live weather data from social media is one aspect of that. We are involved in three research initiatives under the MAELSTROM umbrella, thereby contributing to the energy transition and more sustainable energy generation.