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

Project Links:

https://www.nnergix.com/sentinel-weather/

https://sentinel-weather.com/

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

Average Sustainability Index

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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