Date of Award
Doctor of Philosophy (PhD)
Electrical, Computer & Energy Engineering
Lucy Y. Pao
In above-rated wind speeds, the goal of a wind turbine blade pitch controller is to regulate rotor speed while minimizing structural loads and pitch actuation. This controller is typically feedback-only, relying on a generator speed measurement, and sometimes strain gauges and accelerometers. A preview measurement of the incoming wind speed (from a turbine-mounted lidar, for example) allows the addition of feedforward control, which enables improved performance compared to feedback-only control. The performance improvement depends both on the amount of preview time available in the wind speed measurement as well as the coherence (correlation as a function of frequency) between the wind measurement and the wind that is experienced by the turbine.
This thesis shows how to design an optimal collective-pitch controller that takes both preview time and measurement coherence into account. Simulation results show significantly reduced pitch actuation, improved generator speed regulation, and reduced structural loads compared to several different baseline cases. In addition, linear-model-based results show how the benefit of preview depends on the preview time and measurement coherence.
Effective lidar-based control also requires knowledge of the expected arrival time of the measured wind. Arrival time is the time it takes for the wind to travel from the measurement focus location to the turbine rotor. Arrival time is often assumed to be equal to the distance traveled divided by the average wind speed. This thesis, using field test data, studies deviations from this assumption.
Control implementation across the full range of above-rated wind speeds can be achieved through gain scheduling. The effect of gain scheduling implementation on effective feedforward and feedback gains is not straightforward. This thesis provides a detailed explanation of the effective gains resulting from two different gain-scheduling implementations. It includes an analysis of a simplified version of a nonlinear gain scheduling feedback loop as well as verification through simulation with a full nonlinear controller and turbine model.
Additional topics covered in this thesis include a model-inverse-based analysis of the conditions under which lidar is beneficial, a breakdown of the maximum useful amount of preview time by its different uses, and a comparison of two lidar-based individual pitch controllers.
Dunne, Fiona, "Optimizing Blade Pitch Control of Wind Turbines with Preview Measurements of the Wind" (2016). Electrical, Computer & Energy Engineering Graduate Theses & Dissertations. 125.