Abstract

A gain-scheduled feedforward controller, based on pseudo-LIDAR (light detection and ranging) wind speed measurement, is designed to augment the baseline feedback controller for wind turbine’s load reduction in above rated operation. The pseudo-LIDAR measurement data are generated from a commercial software – Bladed using a designed sampling strategy. The nonlinear wind turbine model has been simplified and linearised at a set of equilibrium operating points. The feedforward controller is firstly developed based on a linearised model at an above rated wind speed, and then expanded to the full above rated operational envelope by employing gain scheduling strategy. The combined feedforward and baseline feedback control is simulated on a 5 MW industrial wind turbine model. Simulation studies demonstrate that the proposed control strategy can improve the rotor and tower load reduction performance for large wind turbines.

Highlights

  • 1.1 Wind turbine load rejection strategiesWith the increase of installed wind power capacity over the past few years, operation and maintenance of wind energy production becomes a critical issue in wind industry

  • Potential improvements on reducing the turbine loads and pitch control actions in above rated operation have been discussed on these light detection and ranging (LIDAR) assisted feedforward control strategies

  • Advanced control techniques such as model-based predictive control (MPC) employing wind speed measurement has been investigated, in which the future events of the wind turbine based on the preview wind measurement are predicted for a better wind disturbance rejection response of the controller

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Summary

Wind turbine load rejection strategies

With the increase of installed wind power capacity over the past few years, operation and maintenance of wind energy production becomes a critical issue in wind industry. A possible solution to this problem is to employ the incoming wind disturbance information into the control system in advance so that the controller can respond to the disturbance and thereby alleviate the induced loads timely This method depends on direct and accurate wind measurement to estimate the disturbance. Comparing to the wind anemometer, a LIDAR device can emit laser beams to the front of the turbine and measure and provide the incoming wind speed information before the wind reaches the turbine. This allows extra time for the controller to make a response. Information on LIDAR basics can be found in recent literature, for example, LIDAR configurations and turbine-mounted options[10, 11], data analyses from LIDAR measurement[12], field testing studies[11, 13]

LIDAR measurement in wind turbine control
Pseudo-LIDAR data generation
Baseline wind turbine model
Linearisation of wind turbine model
Validation of linearised models
Baseline control system
Feedforward controller design
Stable inversion of the turbine dynamics
Gain scheduling
Simulation studies
High wind speed region
Conclusions

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