Intelligent control of doubly‐fed induction generator systems using PIDNNs

As wind energy becomes one of the fastest growing renewable energy resources, the control of large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. In this paper, an adaptive neural pitch angle control strategy is proposed for the variable-speed wind turbines (VSWT) operating in pitch control region. The control objective is to maintain the rotor speed and generator power at the prescribed reference values in the presence of external disturbance, without the need of the information of system parameters and aerodynamics. First, the order of the system dynamics is increased by defining a filtered regulation error. By this means, the non-affine characteristics of the VSWT model is transformed into a simple affine control problem and thus the feedback linearization technique can be employed. The continuousness of control signal is also guaranteed to relax the requirement on the bandwidth of actuators, and the mechanical load on pitching systems is reduced. Subsequently, an online learning approximator (OLA) is utilized to estimate the unknown nonlinear aerodynamics of the wind turbine and extend the practicability of the proposed adaptive parameter-free controller. In addition, a high-gain observer is implemented to obtain an estimation of rotor acceleration, which rejects the need of additional sensors. Rigid theoretical analysis guarantees the tracking of rotor speed/generator power and the boundedness of all other signals of the closed-loop system. Finally, the effectiveness of the proposed scheme is testified via the Wind Turbine Blockset simulation package in Matlab/Simulink environment. Moreover, comparison results reveal that the introduced solution is able to provide better regulation performance than the conventional PI counterpart.

Section: Control Objectivementioning

confidence: 99%

Section: Control Objectivementioning

confidence: 99%

Section: Dynamics Of Regulation Errormentioning

confidence: 99%

“…Differentiating r and using model (14), the dynamics of the rotor speed can be written in terms of the filtered regulation error aṡ…”

Section: Dynamics Of Regulation Errormentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Adaptive Continuous Neural Pitch Angle Control for Variable‐Speed Wind Turbines

Jiao

Yang

Fu³

et al. 2018

Robust Wind Speed Estimation and Control of Variable Speed Wind Turbines

Barambones

2018

In this work, a robust control scheme for variable speed wind turbine system that incorporates a doubly feed induction generator is described. The sliding mode controller is designed in order to track the optimum wind turbine speed value that produces the maximum power extraction for different wind speed values. A robust sliding mode observer for the aerodynamic torque is also proposed in order to avoid the wind speed sensors in the control scheme. The controller uses the estimated aerodynamic torque in order to calculate the reference value for the wind turbine speed. Another sliding mode control is also proposed in order to maintain the dc-link voltage constant regardless of the direction of the rotor power flow. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally, the simulation results show that the proposed control scheme provides a high-performance turbine speed control, in order to obtain the maximum wind power generation, and a high-performance dc-link regulation in the presence of system uncertainties.

Robust CRONE Design for a Variable Ratio Planetary Gearing in a Variable Speed Wind Turbine

Feytout¹,

Lanusse²,

Sabatier³

et al. 2013

Most installed wind turbines have traditional architectures: doubly‐fed asynchronous machine or direct drive with full conversion, both containing several levels of control composed of PI controllers. In our application, a robust 3rd‐generation‐CRONE controller (CRONE approach is a robust control methodology based on fractional order differentiation) is used to manage a planetary gearing ratio upstream of a synchronous generator directly connected to the grid. Thus, the speed of the Low‐Speed Shaft is controlled and unlike other architectures, no system of power electronics is required for conversion.