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Floating offshore wind turbines (FOWTs) experience multiple degree-of-freedom (DOF) motion as a result of the non-linear interactions between the aerodynamic and hydrodynamic forces exerted on the turbine rotor and the floating platform, respectively, which create complex dynamics for FOWT operations and, in turn, variability in rotor angular speed and power capture. In this work, wind tunnel experiments are performed with a down-scaled FOWT model installed on top of a robotic emulator that reproduces 4-DOF motions. Rotor rotational speed, ω, and power capture are measured for pitch motions with different amplitudes and frequencies. These experimental data are first analyzed, then used for the validation of a non-linear dynamic analytical model that predicts the variation in ω and power capture by leveraging the aerodynamic quasi-steady assumption, namely, the FOWT power curve measured under static conditions and null pitch angle is used to predict operations under dynamic conditions. The results show that good accuracy is generally achieved with the analytical model. However, dynamic aerodynamic effects occur during pitch motion that can jeopardize the accuracy of the analytical model, especially with increasing ω, motion amplitude, and in correspondence with pitch angles where the inversion of the motion direction occurs. Furthermore, it is found that these dynamic aerodynamic effects can be accurately predicted through a random forest model by providing as input pitch angle, velocity, and acceleration of the incoming wind. Among the different FOWT motion parameters, the pitch angle is found to be the most influential factor for the magnitude of the dynamic aerodynamic effects. 

Abstract Quantification of the performance degradation on the annual energy production (AEP) of a wind farm due to leading‐edge (LE) erosion of wind turbine blades is important to design cost‐effective maintenance plans and timely blade retrofit. In this work, the effects of LE erosion on horizontal axis wind turbines are quantified using infrared (IR) thermographic imaging of turbine blades, as well as meteorological and SCADA data. The average AEP loss of turbines with LE erosion is estimated from SCADA and meteorological data to be between 3% and 8% of the expected power capture. The impact of LE erosion on the average power capture of the turbines is found to be higher at lower hub‐height wind speeds (peak around 50% of the turbine rated wind speed) and at lower turbulence intensity of the incoming wind associated with stable atmospheric conditions. The effect of LE erosion is investigated with IR thermography to identify the laminar to turbulent transition (LTT) position over the airfoils of the turbine blades. Reduction in the laminar flow region of about 85% and 87% on average in the suction and pressure sides, respectively, is observed for the airfoils of the investigated turbines with LE erosion. Using the observed LTT locations over the airfoils and the geometry of the blade, an average AEP loss of about 3.7% is calculated with blade element momentum simulations, which is found to be comparable with the magnitude of AEP loss estimated through the SCADA data.