Modeling of rain-induced erosion of wind turbine blades within an offshore wind cluster

Abstract This study investigates the influence of wind turbine wakes on the incubation period of leading-edge erosion in offshore environments within an offshore wind cluster. The analysis is performed on a cluster of 250MW+ offshore wind farms mainly consisting of wind turbines with over 5MW rated power. The incubation time of the leading-edge erosion is determined for each turbine from wind-and-rain statistics, coating properties, and tuned analytical wake models. The wind speed, wind direction, and conditional probability of the rain are determined using 25 years of ERA5 reanalysis data. Droplet size distributions are derived from Best’s analytical distribution, which provides a probability distribution of the rain droplet size for a given rainfall intensity. For each wind turbine, the inflow speed and rotor speed are calculated using the TurboGaussian wake model. In addition, an analytical surface fatigue model is used to estimate the short-term erosion damage rates. By multiplying the short-term erosion damage rate with their respective join probabilities, equivalent damage is obtained the inverse of which will indicate the coating lifetime. The results indicate that variability in the coating lifetime across the wind farms can reach up to 35%. Notably, turbines that are predominantly positioned upstream are found to have the shortest coating lifetimes.