Control inteligente para optimizar la extracción de potencia y reducir vibraciones en sistemas eólicos offshore

Resumen

This research analyzes the performance of a hybrid control strategy in the maximum power point tracking (MPPT) region and the effect on structural vibration reduction in a 5MW floating offshore wind turbine (FOWT). In these wind systems, different disturbance sources influence the stability of the wind turbine. These elements that alter the efficient operation of the wind turbine, include the non-linear nature of the machine, turbulent winds, and waves that change the structural stability of the device. The controller in this study uses an adaptive radial basis function neural network (RBNN) to regulate the electromagnetic torque, which influences the speed and output power. In addition, this torque is complemented by incorporating a conventional PID control that focuses on reducing the tower motion. The controller is optimized with the use of a genetic algorithm. The performance of the controller is validated against the OpenFast torque controller, achieving a higher output power and at the same time a decrease in the effect of vibrations.