New in wind data: Whiffle’s highly accurate atmospheric modelling 

Whiffle’s atmospheric modelling is now available directly in Vind AI. Powered by large-eddy simulations (LES), Whiffle’s modelling delivers quick, reliable simulations of local wind conditions specific to a given wind farm site.

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With Whiffle integrated in Vind AI, you can: 

• Design based on accurate wind data from the start: Whiffle provides quick and reliable simulations of local wind conditions specific to a given wind farm site. You no longer have to wait for measurements to gain the insights of precise site-specific data.
• Complete more precise scenarios much faster: Whiffle’s simulations complete in hours instead of days. Combined with Vind AI’s scenario engine, you can test multiple layouts and conditions in far less time.
• Access high-fidelity wind data in one place: Accessing Whiffle’s data directly inside Vind AI, alongside data from our existing specialist data providers and more than 6000 built-in data layers, means you no longer need to juggle multiple data sources manually.

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Next steps: This is just the beginning of the Whiffle integration including integrating the Whiffle Atlas. Read our press release to find out more.

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New in optimisation: Turbine reduction 

We’ve just added a new optimisation method called Turbine reduction, a powerful tool for refining your existing layouts.

Turbine reduction works on layouts that already exist. Simply specify the number of turbines you want to keep, and Vind AI will figure out which turbines to remove to minimise AEP losses, without touching the remaining turbines at all.

At the beginning of a project, it is common to start with a large number of turbines. As the project finance becomes clearer and restrictions stricter, we know that the project may experience a need to reduce the number of turbines with little change in the design layout. That is why we just added a new optimisation method: Turbine reduction.

It’s not as simple as removing the lowest-producing turbines. Often, some turbines produce a lot individually but also induce significant wake losses on others. Turbine reduction intelligently accounts for these interactions, keeping your layout efficient and optimised.

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GIS update: Handle large data with ease

We’ve also improved the way Vind AI handles large data files. The new crop input modal currently works for:

• GIS layers larger than 200 MB
• WAsP wind resource grids (WRG)
• ASCII grid files

Thanks to streaming support, you can now work with extremely large GIS datasets, potentially up to 5 GB, without waiting, making it faster and smoother to bring your real-world data into the platform. 

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