In a significant advancement for the wind energy sector, researchers have developed a dynamic yaw model that promises to enhance the efficiency and power output of wind farms. This innovative approach, spearheaded by Genevieve M. Starke from the National Wind Technology Center at the National Renewable Energy Laboratory in Golden, Colorado, utilizes a graph-based model to analyze how changes in yaw— the rotation of the turbine to face the wind—affect the performance of wind turbines.
The model fundamentally shifts the way we understand turbine interactions within a wind farm. By treating each turbine as a node in a graph and the interactions between them as edges, Starke and her team have created a more precise depiction of how wind turbine wakes—areas of reduced wind speed behind a turbine—respond to changes in yaw. This model includes a groundbreaking analytical description of these wakes, allowing for a more accurate representation of the velocity deficits experienced by downstream turbines.
Starke emphasizes the practical implications of this research, stating, “By integrating real-time data into our dynamic yaw model, we can significantly improve the control of wind farms, ultimately leading to increased energy production.” This real-time coupling not only enhances the accuracy of the model but also allows for better decision-making in operational settings, which can lead to substantial economic benefits for wind farm operators.
The research further validates its findings through large-eddy simulations, which are crucial for understanding turbulent flows in wind energy applications. This validation process ensures that the model can be reliably used in real-world scenarios, paving the way for its integration into optimal control loops for managing power output across wind farms.
The commercial impacts of this research are profound. As the demand for renewable energy sources continues to grow, optimizing the performance of wind farms becomes increasingly critical. Enhanced yaw control can lead to higher energy yields, reduced operational costs, and ultimately, a more competitive position in the energy market.
This research, published in the journal ‘Wind Energy’ (translated from German as ‘Windenergie’), marks a pivotal step toward smarter and more efficient wind energy systems. By leveraging advanced modeling techniques, the wind energy sector can look forward to a future where energy production is maximized, benefiting both operators and consumers alike. For more information on Starke’s work, visit National Renewable Energy Laboratory.
