Step-by-step manual

This is a step-by-step manual of how to use the Open Power System Data platform. Different users have different requirements: some want simple, direct access of data files, others are interested in all methodological detail. Choose yourself:

No frills: “I want a simple download”

You want to go straight ahead and download data right away? The data platform’s cover page provides direct download links to all Data Packages which include a CSV file with data and a JSON file with metadata. With one click you are done.

Curious: “I want to know the essentials”

You want to read data definitions, access metadata, read the model documentation, get data in different file formats, download previous versions of the data, review the original input data or learn about our data sources? We provide European power system data in five Data Packages. Each package comes with a info page that provides all these things:
1. Conventional power plants
2. National generation capacity
3. Renewable power plants
4. Time series
5. Weather data

Expert: “I want to know all the details”

You want to understand the details of how we download, process, and aggregate data? Have a look at our Jupyter Notebooks on GitHub or nbviewer. The notebooks contain human-readable documentation as well as the Python code that we use for processing. You can read both documentation and code directly in your web browser – no need to install any software. The info page of each data package links directly to the respective Notebook using the documentation link:
1. Conventional power plants
2. National generation capacity
3. Renewable power plants
4. Time series
5. Weather data

Developer: “I want to run the scripts myself”

You want to run our scripts locally on your computer? We are publishing the full script code used to generate the data in Jupyter Notebooks, so you are able to download, adjust and re-run our Notebooks. All notebooks are published under an open license, so you are allowed to do so as well.  This enables users not only to verify our data clean-up process, but also to customize it to their own needs. To run scripts locally, follow the tutorial to run OPSD scripts. We invite you to contribute to the platform.