4Cast GmbH & Co. KG
Annekatrin Kirsch serves as the Head of Product at 4cast since 2019, where expertise lies in scientific meteorology with a focus on intermittent energy source modeling. In this role, Annekatrin Kirsch drives innovation by developing machine learning solutions for accurate renewable energy predictions. Prior to this position, Annekatrin Kirsch held roles including Teamleiterin and wissenschaftliche Mitarbeiterin at the Leibniz-Institut für Atmosphärenphysik from 2011 to 2017. Annekatrin Kirsch obtained a Diplom-Meteorologin degree in Meteorologie from Freie Universität Berlin between 2003 and 2010.
This person is not in any teams
This person is not in any offices
4Cast GmbH & Co. KG
Wind energy in particular is notoriously difficult to predict. Regional, small-scale effects such as vegetation or neighboring turbines influence electricity generation on a large scale. This makes predictions based solely on weather data unreliable because their geographic resolution is too coarse. The solution is to use your historical production data. All these effects are hidden in there! Our algorithms can read your data like an open book and infer the regional characteristics of the location. Supplemented by weather data from a variety of sources, we apply machine learning technology to your production data to learn an optimal model that meets your specific needs. Our specialty is learning analytic models using Datacentric AI, Meta Search Strategies, and other methods, but our algorithms also have all the current deep learning techniques. The result is prediction of unprecedented precision. Whether you need highly accurate intraday forecasts to minimize financial losses in energy trading, or short-term forecasts to accurately estimate power production to meet regulatory requirements, choose 4cast.
Employees
11-50