Site-specific day-ahead forecasting of wind resources at scale – Hans Harhoff Andersen, Vestas Wind Systems


Power forecasting for renewable energy sources is a vital tool in enabling the green energy transition. We recently re-implemented the Vestas power forecasting system to leverage the latest machine learning algorithms and use cloud technologies for higher reliability and scalability. We will present the challenges and our proposed solutions as well as the benefit of modularized models.

Key Takeaways

  • How to scale machine learning to large datasets and many partitioned models
  • How to enable non-coders to configure specialized models
  • How to work across the organization when doing ML

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