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OpensSTF OpenSTEF provides automated machine learning pipelines to deliver accurate, self-correcting and explainable forecasts of the load on the grid for the next 48 hours.

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Description

The energy transition poses new challenges to all parties in the energy sector. For grid operators, the rise in renewable energy and electrification of energy consumption leads to the capacity of the grid to near its physical constraints. Forecasting the load on the grid in the next hours to days is essential for anticipating on local congestion and making the most of existing assets.  

OpenSTF OpenSTEF provides a complete software stack which forecasts the load on the electricity grid for the next hours to days. Given a timeseries of measured (net) load or generation, a fully automated machine learning pipeline is executed which delivers a probabilistic forecast of future load. This works for energy consumption, (renewable) generation or a combination of both. OpenSTF OpenSTEF performs validation on the input data, combines measurements with external predictors such as weather data and market prices, trains any scikit-learn compatible machine learning model, and delivers the forecast via both an API and an (expert) graphical user interface. The stack is based on open source technology and standards and is organized in a microservice architecture optimized for cloud-deployment.

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Screenshot of the operational dashboard showing the key functionality of OpenSTFOpenSTEF

Find the latest information on the project on the projects website.

Want to join the discussion? Join our Teams channel.

You can also watch a video about OpenSTEF instead of reading about the project

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urlhttps://www.youtube.com/watch?v=VAlo4vC1ccw

Documentation

Technical documentation can be found here

Roadmap

The roadmap can be found here

Technical steering committee

More information on the OpenSTEF Technical steering committee can be found here.


Repositories

LinkDescription
openstfOpenSTEFAutomated Machine Learning Pipelines. Builds the Open Short Term Forecasting package
openstfOpenSTEF-dbcProvides (company specific) database connector for the OpenSTF OpenSTEF package
openstfOpenSTEF-offline-example

Provides Jupyter Notebooks showing how to use OpenSTF OpenSTEF and apply it's functionality to your usecase

openstfOpenSTEF-referenceDeploy the entire OpenSTF OpenSTEF stack on your machine. Provides a reference implementation of the OpenSTF stackOpenSTEF stack

License

This project is licensed under the Mozilla Public License, version 2.0.

Contributing

Please read CODE_OF_CONDUCT.md, CONTRIBUTING.md and PROJECT_GOVERNANACE.md for details on the process for submitting pull requests to us.

Contact

Please read SUPPORT.md for how to connect and get into contact with the OpenSTEF project