Precipitation in the context of wind turbine blade erosion

In recent years the reported cases of leading-edge erosion (LEE) of wind turbine blades, especially offshore, have increased. LEE is an umbrella term for damages on the leading edge of turbine blades. The impact of particles, such as the precipitation particles rain and hail, causes stresses in the material, which leads first to rougher surfaces and tiny cracks and then to visible damages.

These damages affect the aerodynamic efficiency causing a decrease in the annual energy production. As a last consequence, the turbine blades must be replaced, if the damages are not repaired in time. To avoid unforeseen repair and maintenance costs, more realistic blade lifetimes calculations are needed.

In addition, tailored mitigation strategies are requested to reduce LEE and its negative effect on the rate of return. The first main objective of this PhD thesis was the investigation of the spatio-temporal behavior of precipitation in the North Sea and Baltic Sea area, the influencing factors and their affect on blade lifetime.

LEE models and related blade-lifetime calculations benefit from a better understanding of precipitation as inappropriate model assumptions can be detected. The second main objective was to develop a strategy for integrating precipitation data in the erosion-safe mode concept. This is using a turbine control to decrease the wind turbine tip-speed in case the rain rate exceeds a certain threshold.

The erosion-safe mode reduces the impact speed of particles and thereby reduces the stresses and related damages on the leading edge. Time series of precipitation from disdrometers and rain gauges and other meteorological parameters with a duration of one up to six years were analysed from several stations located offshore or close to the coast of the North Sea and Baltic Sea.

Variability of the precipitation parameters rainfall amount, rainfall kinetic energy (KE), precipitation type and the reflectivity - rain rate (Z-R) relationship with geographical location and weather type was investigated. In a further step, the influence of drop diameter and wind speed on KE was analysed.

KE combines the parameters drop number, drop diameter and drop fall speed. The same factors are considered in some LEE models. The effect of different drop-diameter parameterisations and rain amounts on blade lifetime was analysed using an existing LEE model. Rain was the dominant precipitation type at all stations.

Comparisons of different precipitation parameters, like rainfall amount and KE, showed variations with geographical location and weather type. The dependence of KE on location and weather type could be explained by differences in the drop-size distribution and this was estimated successfully with the parameters of the Z-R relationship.

Drop diameters contributed with different weight to the cumulative KE, where mid-size drops contributed the most. In addition to that, factors like season and wind speed influenced the drop-size distribution and therefore also KE. This resulted in higher KE values in summer and autumn. For the first time it was shown that blade lifetime calculations are sensitive to the applied diameter parameterisation used for calculating the impact energy.

Further calculations proved that an erosion-safe mode extends blade lifetime by reducing LEE. For an effective use of an erosion-safe mode control, a novel nowcasting method for precipitation was suggested, considering the fall properties of rain. This method allows an active application of the erosion-safe mode, i.e., a decrease of the tip speed before the precipitation impacts.

These results highlight the variety of precipitation conditions, their influencing factors and show their relevance for LEE. In future, the results might be included in site assessment to allow realistic LEE predictions. Furthermore, the development of an innovative precipitation nowcasting is an important step towards the field scale implementation of the promising erosionsafe mode.