At the Wind Europe Technology Workshop 2025, held in Istanbul, Turkey, on 19–20 June, more than 400 experts gathered to explore the latest developments in resource assessment and wind farm operations. A key theme emerging from the event was the growing role of data-driven approaches in wind, weather and energy forecasting. These tools are enabling a shift away from traditional, computationally intensive numerical weather models toward faster, more efficient, yet equally accurate methods. 

Among the participants was DHI, presenting results from the European project DTWO, with a focus on the use of numerical models and machine learning to analyse wave and ocean current fields at operational offshore wind farms. 

“The event was a great opportunity to meet project partners and offshore wind experts who are interested in combining numerical models with machine learning,” said Ioannis Koumaniotis, Metocean Engineer at DHI and part of the DTWO research team. “Results presented a fast and accurate methodology to generate and analyse wave and ocean flow fields over two operating wind farms for the DTWO project.”, added Koumaniotis. 

As offshore wind becomes a pillar of the energy transition, these advances signal a shift toward more intelligent, reliable, and responsive forecasting capabilities — essential for optimizing performance and ensuring the resilience of future energy systems. 

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