On-demand webinar

Why wind engineering models fall short as offshore projects scale - and how DNV's new model closes the gap

Over and underprediction of energy yield remains a major risk in offshore wind financing, especially as wind projects scale into multi-GW clusters and neighbouring-project effects become harder to quantify. Discover how DNV’s latest approach to turbine interaction modelling is addressing this growing challenge.

Learn how DNV offshore wind experts are addressing this challenge with CFD.ML — DNV’s new turbine interaction model — and how it can be applied in early-stage wind energy assessments to help you and your team better capture losses, reduce under or overprediction risk, improve yield accuracy, and strengthen project confidence ahead of financial close. 

Webinar highlights:

  • The growing gap between engineering models and high‑fidelity CFD
  • How CFD.ML works and what it captures that engineering models miss
  • CFD.ML in practice
  • How to use CFD.ML the way DNV does
  • How CFD.ML integrates with VindAI, explained by the VindAI team

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