• wind speed estimation;
  • wind direction estimation;
  • blade-effective wind speeds;
  • extreme event recognition;
  • extreme event control;
  • load reduction


This paper focuses on the problem of extreme wind gust and direction change recognition (EG&DR) and control (EEC). An extreme wind gust with direction change can lead to large loads on the turbine (causing fatigue) and unnecessary turbine shutdowns by the supervisory system caused by rotor overspeed. The proposed EG&DR algorithm is based on a non-linear observer (extended Kalman filter) that estimates the oblique wind inflow angle and the blade effective wind speed signals, which are then used by a detection algorithm (cumulative sum test) to recognize extreme events. The non-linear observer requires that blade root bending moments measurements (in-plane and out-of-plane) are available. Once an extreme event is detected, an EEC algorithm is activated that: (i) tries to prevent the rotor speed from exceeding the overspeed limit by fast collective blade pitching; and (ii) reduces 1p blade loads by means of individual pitch control algorithm, designed in an ℋ optimal control setting. The method is demonstrated on a complex non-linear test turbine model. Copyright © 2009 John Wiley & Sons, Ltd.