How Icing affects Wind Power Production
Regions of high altitude or latitude, such as Northern and Central Europe, Northern America and Asia have wind plants operating in cold climates and they are exposed to atmospheric ice, which causes problems for the wind turbine, such as increase of mechanical loads, premature shut down, reduction of lifetime of the components and power losses.
In the beginning of 2021, a power outage was observed in Texas, US, and reported by Reuters: Icy weather chills Texas wind energy as deep freeze grips much of U.S. Recently, I’ve published an article about this topic that is on the news today:
After spending a few years in Russia and Finland, and studying about energy technologies and focusing on wind turbines, I am here to share some observations and results during my research.
The artic region plays an important role of wind production in Scandinavia and the estimated potential for Finland is at least 3 GW, but it carries some challenges for its exploitation from the initial site assessment, during the construction of the wind plant and during its operation.
Wind turbines are exposed to ice formation in cold weather and this phenomenon causes a variety of problems to the machine, such as increasing of mechanical loads on the turbine’s components and power production losses (Clausen & Giebel, 2017). Furthermore, icing increases possibility of ice throw and unbalance on the rotor, increasing the dynamics loads and noise level and it might lead to premature failure of the system and financial losses (IEA Wind Task 19, 2017).
In cold climates the wind turbine is exposed to icing formation on the rotor, causing a variety of problems for the operation of the machine. For the loss of annual electricity production due to icing, some researchers with different approaches found results up to 10% loss without blade heating , 22% loss using time series of wind speed and icing, while 25% loss was estimated in a wind plant in Sweden.
Types of Ice
Glaze Ice
When the temperature is just below 0 ºC, the wind speed is increasing and the water content in the air is high, ice can be accreted on any surface, and it has a transparent appearance, glassy shiny surface or ice cubes and high density (Hudecz, 2014) and its appearance is seen in the next image.
Rime Ice
The rime ice occurs when the temperature is lower, usually lower than -4 ºC and higher than -20 ºC and the droplet freezes completely with the impact on the object, so it is not spread through the surface (IEA Wind Task 19, 2017). It is white, opaque, and streamlined accretion, and it is more porous, therefore it has a lower density than glaze ice.
Aerodynamic Analysis
The main parameters that affect the aerodynamic performance of a wind turbine are lift and drag coefficients, and the following image shows both coefficients for angle of attack varying from 0 to 10º for a NACA 64618 airfoil series. The bottom graph of is the ratio Drag/Lift per angle of attack, and it is important when analyzing the equations for power coefficients.
It is possible to note that in lower angle of attack the effect of icing is higher, on the other hand for the lift, the icing effect is higher when the angle of attack is 10º. This results refer to the section 9 of a 15 sections blade, and it was used in this analysis because the third part of the blade has a higher impact in power production.
The results show that icing decreases aerodynamic performance of the wind turbine when angle of attack is larger than 5º and it is according to existing trends in literature.
For each angle of attack (α) there is a ratio drag / lift and the tip-to-speed ratio (λ) is varied from 0 to 20 so there is one curve for each combination of α and ratio. Each graph of the clean case has one maximum power coefficient for one combination of α and λ, which is the optimal operational point of the turbine. If there is ice on the blade, the optimum combination of α and λ changes and this is the new optimal operational point of the turbine with ice on its blades. When the values of α and λ of the clean case are applied to the icing case, loss of power production is observed.
For the clean airfoil (graph on the left), the maximum power coefficient is Cpclean = 0.4755, when α = 5º and λ = 5.6. For the icing case (graph on the right), the maximum power coefficient is Cpopt = 0.4526, when α = 0º and λ = 4.6.
There are 3 main results for this analysis: Non-Optimized Cp (Cp,non-opt); α-Optimized Cp (Cp,α-opt); and Fully-Optimized Cp (Cp,opt).
- Non-Optimized Cp: if the same conditions of α and λ of the clean case are applied for the icing case, the obtained power coefficient is Cp,non-opt = 0.4157, represented by the red mark on the graphic below. This value is the non-optimized configuration for the icing case.
- α-Optimized Cp: if only α is optimized, the power coefficient is Cp,α-opt = 0.4499, represented by the yellow mark on the graphic below. This value has optimization only in the angle α.
- Fully-Optimized Cp: if α and λ are optimized, the power coefficient is Cp,opt = 0.4526 and it is represented by the green marks on the graphic below. This value is the optimum configuration for both the icing case, with optimization in the angle α and in the tip-to-speed ratio λ.
The difference between the red and the green is considered as the improvement made by this method.
For a wind turbine, there are 3 regions of operation according to the wind speed:
- Region I: from 0 to 3 m/s (not operating)
- Region II: from 3 to 7,5 m/s (operating with optimum angle of attack α)
- Region III: from 7,5 to 25 m/s (pitch control starts to actuate to keep rated power)
The pitch control starts to actuate when the wind speed reaches the rated wind speed according to the design of the wind turbine. With that, we can visualize the aerodynamic losses in the next graph.
The losses as higher in Region II, where pitch control is not actuating.
Study Case
For the study case, it was considered that a wind turbine does not have any type of anti-icing or deicing system.
Olhava is in the middle Finland and it is the most South location used in this study case, with an average wind speed of 4.57 m/s, average temperature of 2.39 ºC and average relative humidity of 88.21%. The region is known as a good area for wind plants and it has a high number of wind farms close by.
Yearly losses for Olhava shows an oscillation of power losses, varying from 4.3% to 10.6% with an average of 7.1% for the icing case and it is reduced from 2.8% to 7.6% with an average of 4.8% for the optimized case, according to the next graph.
The power curves for Olhava are shown in the next graph and it is clearly visible that the icing component for the non-optimized case has a larger space separating it from the clean component.
As it was expected, the optimization method (green dots) is between the clean (blue dots) and the non-optimized case (red dots), showing the improvement made by the presented method. The separation between the components is more visible in this case comparing to the others.
Conclusions
The power curve shows the component produced when there is no icing more on the left adjacent of the graph (blue dots) and the component on the right adjacent, when there is icing formation (red dots). In theory, the icing component should move to the left, close to the clean component when the optimization method is applied, and this fact was observed in this case.
Thanks for reading it!
LinkedIn Afonso Lugo
