hugorcf / renewable-energy-weather

Predicting wind and solar generation from weather data using Machine Learning

Wind and solar generation from weather data is predicted using a linear regression algorithm and a dataset containing energy production and weather information for Germany during 2016.

More information can be found in my blog post.

Data

The data used in this analysis come from Open Power System Data, a free-of-charge platform with data on installed generation capacity by country/technology, individual power plants (conventional and renewable), and time series data. It can be obtained from:

https://open-power-system-data.org/

The platform contains data for 37 European countries, but here only the data for Germany in 2016 is used. In particular, two datasets are used:

• Time series with load, wind and solar, prices in hourly resolution.
• Weather data with wind speed, radiation, temperature and other measurements. Given the huge amount of data, the Open Power System Data platform provides a CSV file for the German dataset for 2016 and a script to download the data for other countries and years.