Abstract
Wake steering is a promising strategy to mitigate wake-induced losses; however, the joint assessment of power and structural loads under realistic inflow variability remains underdeveloped, and idealized yaw settings may introduce systematic simulation discrepancies. To address these, an evaluation framework is proposed that integrates field experiments with SCADA-driven simulations. Field experiment conducted at an offshore wind farm yielded SCADA data, including power and yaw angle distributions. Simulations are driven by the SCADAmeasured yaw angle distributions, rather than ideal yaw settings, and evaluations are performed for three wind direction sectors (- 5 degrees, 0 degrees, +5 degrees). Farm power and blade root metrics, including maximum load (ML) and damage equivalent load (DEL), are assessed in field measurements and simulations. The experiment yielded an average power gain of 8.3 % for wind speeds of 4-10 m/s, including 4.5 % for 6-7 m/s, with gains concentrated in the rear rows. Using the measured yaw angle distributions in simulations, we quantified the bias introduced by idealized yaw assumptions, which produces mean absolute changes of 6.9 % in power and 10.5 % in flapwise DEL. When comparing wake steering with MPPT, variations in edgewise DEL are small (-0.9 % to +1.0 %), whereas flapwise DEL changes range from -6.1 % to +17 %.