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Wind turbine blade leading edge erosion (LEE) reduces energy production and increases wind energy operation and maintenance costs. Degradation of the blade coating and ultimately damage to the underlying blade structure are caused by collisions of falling hydrometeors with rotating blades. The selection of optimal methods to mitigate/reduce LEE are critically dependent on the rates of coating fatigue accumulation at a given location and the time variance in the accumulation of material stresses. However, no such assessment currently exists for the United States of America (USA). To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. Time series analyses indicate that up to one-third of blade coating lifetime is exhausted in just 360 5-min periods in the Southern Great Plains (SGP). Conversely, sites in the Pacific Northwest (PNW) exhibit the same level of coating lifetime depletion in over three times as many time periods. Thus, it may be more cost-effective to use wind turbine deregulation (erosion-safe mode) for damage reduction and blade lifetime extension in the SGP, while the application of blade leading edge protective measures may be more appropriate in the PNW. Annual total precipitation and mean wind speed are shown to be poor predictors of blade coating lifetime, re-emphasizing the need for detailed modeling studies such as that presented herein. 

An enhanced understanding of the mechanisms responsible for wind turbine blade leading-edge erosion (LEE) and advancing technology readiness level (TRL) solutions for monitoring its environmental drivers, reducing LEE, detecting LEE evolution, and mitigating its impact on power production are a high priority for all wind farm owners/operators and wind turbine manufacturers. Identifying and implementing solutions has the potential to continue historical trends toward lower Levelized Cost of Energy (LCoE) from wind turbines by reducing both energy yield losses and operations and maintenance costs associated with LEE. Here, we present results from the first Phenomena Identification and Ranking Tables (PIRT) assessment for wind turbine blade LEE. We document the LEE-relevant phenomena/processes that are deemed by this expert judgment assessment tool to be the highest priorities for research investment within four themes: atmospheric drivers, damage detection and quantification, material response, and aerodynamic implications. The highest priority issues, in terms of importance to LEE but where expert judgment indicates that there is a lack of fundamental knowledge, and/or implementation in measurement, and modeling is incomplete include the accurate quantification of hydrometeor size distribution (HSD) and phase, the translation of water impingement to material loss/stress, the representation of operating conditions within rain erosion testers, the quantification of damage and surface roughness progression through time, and the aerodynamic losses as a function of damage morphology. We discuss and summarize examples of research endeavors that are currently being undertaken and/or could be initiated to reduce uncertainty in the identified high-priority research areas and thus enhance the TRLs of solutions to mitigate/reduce LEE.