Market Insights

Unlocking the Secrets of Turbulence To Mitigate Its Impact on Turbines

October 13, 2023 by Jake Hertz

A research team took an analytic approach to learn more about turbulence and its impact on wind turbines. 

Just as with airplanes, turbulence has a significant impact on the performance of wind turbines. Yet, to this point, we have yet to develop the technology necessary to account for turbulence and counteract its effects.


Turbulence can negatively impact the performance of wind turbines.

Turbulence can negatively impact the performance of wind turbines. Image used courtesy of the National Oceanic and Atmospheric Administration


To solve this issue, a group of researchers from the University of Oldenburg and Sharif University of Technology recently found valuable new insights into how to mathematically describe turbulence and its impact. 


Turbulence and Its Impact on Wind Turbines

Turbulence, in the context of fluid dynamics, refers to the chaotic and irregular motion of air particles. Unlike laminar flow, where air moves in parallel layers with minimal mixing, turbulent flow involves a complex interplay of swirling eddies and vortices.

For wind turbines, this erratic behavior of air particles imposes unsteady aerodynamic forces on the turbine blades, leading to fluctuations in the mechanical loads and electrical output of the wind turbines. The impact of turbulence on wind turbines manifests in several undesirable ways.

First, it causes rapid fluctuations in the power output, extreme enough that that power output can vary by up to 50% within a matter of seconds. Such abrupt changes not only strain the mechanical components of the turbine but also pose challenges for grid integration. Sudden swings in electrical output can destabilize the power grid, requiring additional balancing measures to maintain stability. 

Second, the control systems of wind turbines, designed to optimize performance, often struggle to adapt to turbulent conditions. These systems frequently switch control strategies, exacerbating the fluctuations in power output and mechanical loads.

The influence of turbulence is most pronounced when wind turbines operate under specific conditions. For instance, during the transition to the rated wind speed – the speed at which the turbine produces its maximum rated power – the control systems switch strategies. This transition is particularly sensitive to turbulence, leading to a high increase in jump amplitude in power output. 


Research Finds New Insights

Recently, a group of researchers from the University of Oldenburg and Sharif University of Technology took an innovative approach to address the challenges posed by turbulence in wind turbines. 

Specifically, the group employed stochastic differential equations (SDEs) to model the power conversion process and mechanical loads. The SDEs were constructed with both deterministic and stochastic terms, the latter capturing the highly fluctuating behavior of the turbines. This allowed them to dissect the noise affecting the turbines into two distinct categories: continuous diffusion noise and discontinuous jump noise.


Wind power time series data over the course of ten minutes.

Wind power time series data over the course of ten minutes. Image used courtesy of Lin et al.


Continuous diffusion noise is defined as random fluctuations that occur in a continuous manner. It's akin to the "background noise" in the system and is generally easier to manage or filter out in control systems. Discontinuous jump noise, on the other hand, is more abrupt and represents sudden changes or "jumps" in the system's behavior. These jumps are particularly challenging to manage because they can occur suddenly and have a significant impact on the turbine's performance and the electrical grid.


Why It Matters

According to the researchers, the findings of this study are significant. The team believes that identifying and understanding these two types of noise can enable the development of more sophisticated control systems that can better manage these fluctuations. For example, if a control system is aware that discontinuous jumps are likely to occur under certain conditions, it can preemptively adjust to mitigate the impact.