TY - JOUR

T1 - Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades

AU - Castorrini, Alessio

AU - Barnabei, Valerio F.

AU - Domenech, Luis

AU - Šakalytė, Asta

AU - Sánchez, Fernando

AU - Campobasso, M. Sergio

PY - 2024/6/30

Y1 - 2024/6/30

N2 - Leading edge erosion of wind turbine blades is a major contributor to wind farm energy yield losses and maintenance costs. Presented is a multidisciplinary framework for predicting rain erosion lifetimes of wind turbine blades. Key aim is assessing the sensitivity of lifetime predictions to: modeling aspects (material erosion model, blade aerodynamics), input data and/or their preprocessing (joint frequency distribution of wind speed and droplet size based on synchronous site-specific measurements versus frequency distribution generated with partly site-agnostic modeling standards, wind speed records of nacelle anemometer or extrapolated at hub height from met masts), and environmental conditions (UV weathering). The analyses consider a Northwest England onshore site where a utility-scale turbine is operational, focus on a reference 5 MW turbine assumed operational at the site, and use a typical leading edge coating material. It is found that the largest variations in erosion lifetime predictions are due to material erosion model (based on rain erosion test data or fundamental material properties) and wind and rain model (measurement-based joint wind speed and droplet size distribution or standard-based modeled distribution). The use of joint wind and rain distribution also enables identifying wind/rain states with highest erosion potential, knowledge paramount to deploying erosion-safe turbine control.

AB - Leading edge erosion of wind turbine blades is a major contributor to wind farm energy yield losses and maintenance costs. Presented is a multidisciplinary framework for predicting rain erosion lifetimes of wind turbine blades. Key aim is assessing the sensitivity of lifetime predictions to: modeling aspects (material erosion model, blade aerodynamics), input data and/or their preprocessing (joint frequency distribution of wind speed and droplet size based on synchronous site-specific measurements versus frequency distribution generated with partly site-agnostic modeling standards, wind speed records of nacelle anemometer or extrapolated at hub height from met masts), and environmental conditions (UV weathering). The analyses consider a Northwest England onshore site where a utility-scale turbine is operational, focus on a reference 5 MW turbine assumed operational at the site, and use a typical leading edge coating material. It is found that the largest variations in erosion lifetime predictions are due to material erosion model (based on rain erosion test data or fundamental material properties) and wind and rain model (measurement-based joint wind speed and droplet size distribution or standard-based modeled distribution). The use of joint wind and rain distribution also enables identifying wind/rain states with highest erosion potential, knowledge paramount to deploying erosion-safe turbine control.

KW - Blade leading edge erosion

KW - Modeling of material erosion by rain

KW - Wind speed and droplet size joint frequency distribution

KW - Anemometer and disdrometer measurements

KW - coating material weathering

KW - wind energy

U2 - 10.1016/j.renene.2024.120549

DO - 10.1016/j.renene.2024.120549

M3 - Journal article

VL - 227

JO - Renewable Energy

JF - Renewable Energy

SN - 0960-1481

M1 - 120549

ER -