This study presents a novel method to characterize the aerodynamic flow state on wind turbine blades using eTellTale (eTT) sensors. Deployed on two Vestas V27 turbines, the sensors show that attached flow increases energy production by 15 %, while detached flow reduces it by 30 %. Results indicate that 15 % of potential power is lost during 33 % of operating time, highlighting opportunities for improved real-time turbine control.

Offshore wind farms face the challenge of optimization among many parameters influencing key performance indicators. This research introduces a novel farm optimization framework that enhances flexibility, accuracy, and uncertainty quantification in offshore wind farm design and operation. The proposed work has the key innovation in the ability to translate technical functions into socio-economic objectives, where stakeholders can dynamically weigh these objectives based on their preferences.