Design of Nonlinear Controllers for Variable Speed Variable Pitch Wind Turbine

Abstract

In recent years, wind energy emerges as one of the prominent renewable energy source because of environmental, social and economical benefits. The wind turbines (WT) are classified as fixed speed wind turbine (FSWT) and variable speed wind turbine (VSWT). Compared to FSWT, VSWT offers many advantages such as improved energy capture, reduction in transient load and better power conditioning. In VSWT, the operating regions are classified into two major categories, i.e., below and above rated wind speed. At below rated wind speed, the main objective of the controller (i.e. torque control) is to optimize the wind energy capture by avoiding the transients in the turbine components; especially in the drive train. Whereas, at above rated wind speed, the major objective of the controller (i.e. pitch control) is to maintain the rated power of the WT. At below rated wind, speed the control problem is that the WT rotor should track the optimal rotor speed for extracting the maximum power. This can be achieved by adjusting the generated torque, which is derived from estimated wind speed. So, exact estimation of the wind speed plays one of the major roles in deriving the maximum power from the VSWT. In general, wind speed is measured by the anemometer for deriving the optimal rotor speed to adjust the control input, i.e., generator torque, but the anemometer only measures the single wind speed, i.e., at the point of installation, which is not the accurate effective wind speed. At the same time, anemometer increases the overall cost, maintenance and reduces the reliability of the entire systems. In this work, estimation of effective wind speed is achieved by using different nonlinear estimation algorithms such as Modified Newton Rapshon (MNR), Neural Network trained with different algorithms, and nonlinear time series estimation. This work presents the combination of linear and nonlinear controllers for variable speed variable pitch wind turbines (VSVPWT) operating at below and above rated wind speeds. The mathematical model of the turbine is derived from two mass model, which deal with flexible modes induced by low speed shaft stiffness. The performances of the controllers are tested with nonlinear FAST (Fatigue, Aerodynamics, Structures, andTurbulence) WT dynamic simulation. The WT simulations are performed in three different cases of wind speed profiles such as below rated wind speed (region-2), above rated wind speed (region-3) and a smooth transition between these two wind speeds (region-2.5). Initially, the conventional control technique such as Aerodynamic torque feed forward (ATF) and Indirect Speed Control (ISC) are adapted to the WT. However, the performance measures of those techniques do not take into account the dynamical aspect of the wind and aero turbine, leading to significant power loss. In addition, it was found that they were not robust with respect to disturbances. In order to overcome the above drawbacks, nonlinear controllers i.e. sliding mode control (SMC), integral sliding mode control (ISMC) and terminal sliding mode (TSMC) have been applied. At region 3 the main aim is to prevent excess power and to mitigate the load using pitch control. There is no standard method to operate WT in transition region i.e. region 2.5 which is between region 2 and 3. This work discusses about the use of a nonlinear control i.e. ISMC and TSMC in region 2 and fuzzy based proportional integral (PI) control in region 3. The benefit of using this combination is analysed for the point of how much electrical energy can be gained in transition region with reduced variation in pitch angle and generator speed. The controllers for WT are tested with different types of wind speed profiles and in the presence of sensor and actuator faults. The thesis concludes that higher tracking dynamic will ensure maximum power capture at the cost of high turbulence in the control action. Conversely a slower tracking dynamic ensures smooth torque, i.e., less transient load on the drive train at the cost of low power capture.