PROJECT TITLE :
FX-RLS-Based Feedforward Control for LIDAR-Enabled Wind Turbine Load Mitigation
ABSTRACT :
An adaptive feedforward controller based mostly on a filtered-x recursive least sq. (FX-RLS) algorithm and a non-adaptive feedforward controller based mostly on a zero-section-error tracking control (ZPETC) technique are designed to enhance a collective pitch proportional-integral (PI) feedback controller for wind turbine rotor speed regulation and component load reduction when the wind turbine is working above rated wind speed. The inputs to the adaptive feedforward controller include measurements of the rotor speed error and also the incoming wind speed, where wind speed would be provided by a industrial lightweight detection and ranging (LIDAR) system. Simulation results are primarily based on comparison with a PI feedback only controller. Simulations show that augmenting the baseline PI feedback management with ZPETC feedforward control improves the blade hundreds but worsens the tower masses. The FX-RLS feedforward algorithm provides better performance than both the baseline PI feedback and therefore the ZPETC feedforward in both tower (fore-aft and facet-to-facet) and blade (flapwise and edgewise) bending moment mitigation. Even with realistic 1 Hz LIDAR data update rate, the FX-RLS feedforward strategy can effectively mitigate the tower and blade bending moment whereas providing higher rotor speed tracking and solely a tiny energy drop.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here