Machine learning techniques for energy forecasting
Brief Project Information
Nnergix company uses both satellite data and machine learning (ML) algorithms for more accurate prediction of energy production. The satellite data is generated from satellite images and they are are prepared for large-scale and small-scale weather models.
SDG
Spain
Published in 2013
More information about the project
The Sentinel Weather platform, developed by Nnergix, provides access to historical weather data and weather forecast data around the world and can predict the impact of weather changes on renewable energy capacity through machine learning techniques. By this means, it can predict the amount of power generated per hour, thereby improving power plant efficiency and reducing operating costs.
Sustainability Review
4.0
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Editor's comment for this project's sustainability
Renewable energy sources, such as solar and wind, are highly dependent on weather conditions. Therefore, effective weather forecasting is an essential part of renewable energy production.
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