Model Predictive LIDAR Control of Wind Turbines for Load Mitigation
Translated title
Authors
Term
10. term
Publication year
2011
Submitted on
2011-06-06
Pages
120
Abstract
This master thesis deals with the design of a model predictive controller (MPC) for load mitigation by including LIDAR measurements in the prediction. For simulation purposes a nonlinear model of a wind turbine is derived. The model is validated by its physical characteristics and by comparing it to another model with the same level of detail and a more complex model in the aeroelastic program LACflex. For use in the developed MPC the nonlinear model is linearized. For use together with the developed MPC a LIDAR model is developed. The developed LIDAR model averages wind speed measurements obtained from the wind field by the LIDAR model included in LACflex. A MPC controller that uses LIDAR measurements in the prediction is developed and tested in MATLAB and LACflex. The MPC is tested in MATLAB on the derived nonlinear model, against a benchmark controller consisting of a standard PI controller with additional damping on tower and drive train. In LACflex the MPC is tested on a more complex turbine model and the included PI controller in LACflex as benchmark. Simulation results showed that by including LIDAR in MPC the load can be mitigated and the power can be maintained
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