Probabilistic forecasts have been underused in this context due to complexity related to their interpretation and data volume. To solve this we will create a machine-readable data portal coupled to machine learning algorithms. We will tailor improved weather forecasts to better support the needs of green energy applications.
Our smart solutions optimize specific energy systems based on the latest weather forecast, local observations, and real-time production data from renewable energy. Targeted applications are heating, ventilation and air-conditioning in buildings, battery charging, and solar and wind power applications.
We utilize current knowledge in numerical modelling, data analysis and digitalization to provide optimized decision support for green energy production and consumption by:
- Improving probabilistic short-range weather forecasts.
- Increase energy efficiency with data-driven machine-learning.
- Creating standardized data format and tools for data exchange.
- Exploiting the energy value chain in a transnational market.
The project is coordinated by Swedish Meteorological and Hydrological Institute (Sweden).
Algorithm Energy AB (Sweden)
Rebasian Technologies AB (Sweden)
Finnish Meteorological Institute (Finland)
Nuuka Solutions Oy (Finland)
Estonian Environmental Agency (Estonia)
December 2022 – June 2025.
This project has been awarded funding within the ERA-Net SES Joint Call 2020 for transnational research, development and demonstration projects.