How cloud-computing is unlocking accurate wake modelling
Recent discussions, about offshore wind resource estimation, demonstrated the need for more sophisticated wake models to reduce the risk of overestimating power production. In this context, ZephyScience developed a new computation methodology, empowered by its cloud-computing services.
This topic emerged over the past few months: wake models used up until now by the wind resource community are ignoring the so-called ‘blockage effect’, resulting from the two-way coupling between wind turbines and the atmosphere.
According to DNV-GL, unaccounted losses from the blockage effect can represent up to 4% of the mean annual energy yield. Therefore, an accurate modeling of wake and blockage effects should be implemented, in order to perform correct estimations of future production.
How cloud-computing is unlocking accurate wake modelling
Recent discussions, about offshore wind resource estimation, demonstrated the need for more sophisticated wake models to reduce the risk of overestimating power production. In this context, ZephyScience developed a new computation methodology, empowered by its cloud-computing services.
This topic emerged over the past few months: wake models used up until now by the wind resource community are ignoring the so-called ‘blockage effect’, resulting from the two-way coupling between wind turbines and the atmosphere.
According to DNV-GL, unaccounted losses from the blockage effect can represent up to 4% of the mean annual energy yield. Therefore, an accurate modeling of wake and blockage effects should be implemented, in order to perform correct estimations of future production.
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