Building a blueprint for better wind farms

How to arrange turbines on a wind farm in a way that minimizes wake interactions between them and optimizes energy production is the subject of intense research. But studies can be time-consuming, and standard modeling approaches can be expensive to simulate at scale how power production varies over different wind conditions.

LoCascio et al. developed a model that combines new analytic tools to predict annual energy production with a unique mathematical technique to determine wind farm layout optimization (WFLO). The researchers then analyzed the performance of their model, which they call FLOWERS, in the context of WFLO for wind farms ranging in size from 10 to 250 turbines.

“Even for the small wind farm of 10 turbines, our new approach is about 50 times faster in solving the optimization problem compared with the conventional reference approach,” said author Michael LoCascio. “For the large wind farm of 250 turbines, it is over 4,000 times faster. We’re talking about finding optimal layouts in a second or a minute with our approach compared with hours or even days.”

While its primary benefit is the dramatic increase in speed for simulating wind energy production, the model also simplifies the process of determining optimal turbine layouts, which may help produce more consistent solutions and performance.

“We think these results are exciting for the wind farm design community,” said LoCascio. “The model is relatively simple in its current form, but there could be a lot of benefits to using it early on in the wind farm design process, and we encourage people to give it a try and see the improved performance for themselves.”

Source: “Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients,” by Michael J. LoCascio, Christopher J. Bay, Luis A. Martínez-Tossas, Jared J. Thomas, and Catherine Gorlé, Journal of Renewable and Sustainable Energy (2025). The article can be accessed at https://doi.org/10.1063/5.0237778 .