An Optical Fiber Bundle Sensor for Tip Clearance and Tip Timing Measurements in a Turbine Rig

When it comes to measuring blade-tip clearance or blade-tip timing in turbines, reflective intensity-modulated optical fiber sensors overcome several traditional limitations of capacitive, inductive or discharging probe sensors. This paper presents the signals and results corresponding to the third stage of a multistage turbine rig, obtained from a transonic wind-tunnel test. The probe is based on a trifurcated bundle of optical fibers that is mounted on the turbine casing. To eliminate the influence of light source intensity variations and blade surface reflectivity, the sensing principle is based on the quotient of the voltages obtained from the two receiving bundle legs. A discrepancy lower than 3% with respect to a commercial sensor was observed in tip clearance measurements. Regarding tip timing measurements, the travel wave spectrum was obtained, which provides the average vibration amplitude for all blades at a particular nodal diameter. With this approach, both blade-tip timing and tip clearance measurements can be carried out simultaneously. The results obtained on the test turbine rig demonstrate the suitability and reliability of the type of sensor used, and suggest the possibility of performing these measurements in real turbines under real working conditions.

Sliding Mode Control Strategy for Wind Turbine Power Maximization

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, a sliding mode control for variable speed wind turbine that incorporates a doubly fed induction generator is described. The electrical system incorporates a wound rotor induction machine with back-to-back three phase power converter bridges between its rotor and the grid. In the presented design the so-called vector control theory is applied, in order to simplify the electrical equations. The proposed control scheme uses stator flux-oriented vector control for the rotor side converter bridge control and grid voltage vector control for the grid side converter bridge control. The stability analysis of the proposed sliding mode controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand, that the proposed controller provides high-performance dynamic characteristics, and on the other hand, that this scheme is robust with respect to the uncertainties that usually appear in the real systems.

Robust speed control for a variable speed wind turbine

Modern wind turbines are designed in order to work in variable speed opera-tions. To perform this task, these turbines are provided with adjustable speed generators, like the double feed induction generator (DFIG). One of the main advantages of adjustable speed generators is improving the system efficiency compared with _xed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However, this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. The proposed design also uses the vector oriented control theory in order to simplify the DFIG dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and pa-rameter uncertainties using the Lyapunov stability theory. Finally, the simulated results show on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, which usually appear in real systems.

Adaptive variable structure control law for a variable speed wind turbine

Presentado en el 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11

Sliding mode control law for a variable speedwind turbine

Modern wind turbines are designed in order to work in variable speed operations. To perform this task, wind turbines are provided with adjustable speed generators, like the double feed induction generator. One of the main advantage of adjustable speed generators is improving the system efficiency compared to fixed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. An integral sliding surface is used, because the integral term avoids the use of the acceleration signal, which reduces the high frequency components in the sliding variable. The proposed design also uses the vector oriented control theory in order to simplify the generator dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and parameter uncertainties by using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, that usually appear in real systems.

An adaptive sliding mode control law for the power maximization of the wind turbine system

POWERENG 2011

Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms

This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches including Reinforcement Learning, the best results were obtained using a Particle Swarm Optimization (PSO)-based wind turbine speed setpoint algorithm. A reward improvement of up to 10.67% has been achieved using PSO compared to a constant approach and 0.48% compared to a conventional approach. We conclude that the pitch angle is the most adequate input variable for the turbine speed setpoint algorithm compared to others such as rotor speed, or rotor angular acceleration.