Abstract
The paper presents a nonlinear approach to wind turbine (WT) using two-mass model. The main aim of the controller in the WT is to maximize the energy output at varying wind speed. In this work, a combination of linear and nonlinear controllers is adapted to variable speed variable pitch wind turbines (VSVPWT) system. The major operating regions of the WT are below (region 2) and above rated (region 3) wind speed. In these regions, generator torque control (region 2) and pitch control (region 3) are used. The controllers in WT are tested for below and above rated wind speed for step and vertical wind speed profile. The performances of the controllers are analyzed with nonlinear FAST (Fatigue, Aerodynamics, Structures, and Turbulence) WT dynamic simulation. In this paper, two nonlinear controllers, that is, sliding mode control (SMC) and integral sliding mode control (ISMC), have been applied for region 2, whereas for pitch control in region 3 conventional PI control is used. In ISMC, the sliding manifold makes use of an integral action to show effective qualities of control in terms of the control level reduction and sliding mode switching control minimization.
Highlights
In recent years, wind energy is one of the major renewable energy sources because of environmental, social, and economic benefits
For extracting the maximum power at below rated wind speed the wind turbines (WT) rotor speed should operate at reference rotor speed which is derived from effective wind speed
Nonlinear static and dynamic state feedback linearization control is addressed in [8, 9] where both the single- and two-mass model are taken into consideration and the wind speed is estimated by using Newton Raphson (NR)
Summary
Wind energy is one of the major renewable energy sources because of environmental, social, and economic benefits. Estimation of effective wind speed by an inversion of static aerodynamic model with known pitch angle is discussed in [7]. Nonlinear static and dynamic state feedback linearization control is addressed in [8, 9] where both the single- and two-mass model are taken into consideration and the wind speed is estimated by using Newton Raphson (NR). For above rated wind speed authors in [15] discussed the multivariable control strategy by combining the nonlinear state feedback control for region 2 with linear control for region 3.
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