Rain‐induced leading‐edge erosion (LEE) of wind turbine blades (WTBs) is associated with high repair and maintenance costs. The effects of LEE can be triggered in less than 1 to 2 years for some wind turbine sites, whereas it may take several years for others. In addition, the growth of erosion may also differ for different blades and turbines operating at the same site. Hence, LEE is a site‐ and turbine‐specific problem. In this paper, we propose a probabilistic long‐term framework for assessing site‐specific lifetime of a WTB coating system. Case studies are presented for 1.5 and 10 MW wind turbines, where geographic bubble charts for the leading‐edge lifetime and number of repairs expected over the blade's service life are established for 31 sites in the Netherlands. The proposed framework efficiently captures the effects of spatial and orographic features of the sites and wind turbine specifications on LEE calculations. For instance, the erosion is highest at the coastal sites and for sites located at higher altitudes. In addition, erosion is faster for turbines associated with higher tip speeds, and the effects are critical for such sites where the exceedance probability for rated wind conditions are high. The study will aid in the development of efficient operation and maintenance strategies for wind farms.

Leading edge erosion (LEE) repairs of wind turbine blades (WTBs) involve infield application of leading edge protection (LEP) solutions. The industry is currently aiming to use factory based LEP coatings that can applied to the WTBs before they are shipped out for installation. However, one of the main challenges related to these solutions is the choice of a minimum LEP application length to be applied in the spanwise direction of the WTBs. Generally, coating suppliers apply 10–20 m of LEP onto the blades starting from the tip of the blade using the “rule of thumb”, and no studies in the literature exist that stipulate how these LEP lengths can be calculated. In this study, we extend the scope of a recently developed long-term probabilistic framework to determine the minimum LEP application length required for WTBs to combat rain-induced erosion. A parametric study is performed where different wind turbines with varying power ratings of 2.1 MW to 15 MW at different Dutch sites ranging from inland to coastal are considered. The results of the study show that the LEP application length is sensitive to the choice of the site, as well as the turbine attributes. Further, LEP lengths for WTBs are found to be the highest for turbines installed at coastal sites and turbines with higher power ratings. A detailed investigation is further performed to check the sensitivity of the LEP application length with the wind turbine parameters. The results of the study are expected to provide guidelines to the industry for efficient repair strategies for WTBs.

The presence of rain-induced leading edge erosion of wind turbine blades (WTBs) necessitates the development of erosion models. One of the essential parameters for erosion modeling is the relative impact velocity between rain droplets and the rotating blade. Based on this parameter, the erosion damage rate of a WTB is calculated to estimate the expected leading edge lifetime. The environmental conditions that govern this parameter have site-specific variations, and thus, rain and wind loading on a turbine differ for onshore and offshore locations. In addition, there are wave loads present in the offshore environment. The present paper tries to provide guidelines for erosion modeling and investigates whether there are differences in erosion of blades due to (1) varying rainfall conditions modeled using different droplet size distributions for onshore and offshore locations in combination with (2) winds of varying turbulence intensities and (3) wave-induced loads. Aero-hydro-servo-elastic simulations are carried out for an onshore wind turbine (WT) and a monopile-supported offshore WT. Furthermore, erosion variables such as the relative impact velocities and the associated erosion damage rate of a blade are analyzed for various blade azimuth angles. The study shows that the rainfall intensity and turbulence intensity minorly influence the impact velocity and pressure but have a substantial effect on the overall erosion damage rate. Additionally, a significantly higher erosion damage rate is found for blades exposed to offshore rainfall conditions than for blades under onshore rainfall conditions. Furthermore, no substantial influence on erosion is found because of wave-induced loads.