Comparison of wind turbine LQG controllers using Individual Pitch Control to alleviate fatigue loads

Abstract

This paper focuses on the design of Linear Quadratic Gaussian (LQG) controllers for variable-speed horizontal axis Wind Turbines (WT). These turbines use blade pitch angle and electromagnetic torque control variables to meet specified objectives for Full Load (FL) zone. The main control objectives are to reduce structural dynamic loads and to regulate the power of the WT. The controllers are designed in order to optimize a trade-off between several control objectives. Four different LQG using Individual Pitch Control (IPC) are designed, with Wireless-Sensors (WS) placed at the end of the blades for the last one. Their control model is progressively more complex. The first one takes into account a rigid simple behavior, the second control model considers the first mode of the drive-train flexibility, the third model takes into account the drive-train and tower flexibilities and the fourth that of the blades. Likewise, their optimization criteria consider for each controller a new control objective to alleviate fatigue loads in the drive-train, then, also in the tower and finally also in the blades. The evaluation of the fatigue loads affecting the WT components are based on a Rainflow Counting Algorithm (RFC) and the Miner's rule. The results indicate a significant reduction of fatigue loads especially in the drive-train and the blades when its flexibility is taken into account in the control models. I. INTRODUCTIONS wind turbines become larger, their mechanical components are more flexible, causing an oscillating behavior of some of them. These oscillations accelerate the fatigue of these components. Therefore, it is becoming more and more important for WT controllers to alleviate the amplitude of these oscillations and thus the components fatigue loads, in particular in offshore farms where WT are bigger and maintenance costs higher. This alleviation allows the cost of electricity generated by WT to be reduced in two ways: by allowing the construction of the most expensive components (blades and tower) with less material and by reducing maintenance costs.Consequently, new controllers have to be developed to reduce the fatigue loads of the main components of WT. The Proportional -Integral -Derivative (PID) controller is still the most widely used in industry, controlling over 95% of closed-loop industrial processes. It is also the most used for WT control. In [1], a PI controller has been designed for FL operations in order to alleviate tower loads.

Optimal Design for a Composite Wind Turbine Blade With Fatigue and Failure Constraints

“…Conversely Jureczko et al [12] demonstrated that pure aerodynamic optimization is insufficient when blades become longer than 45 m and the dynamic behavior becomes imperative, mainly because of the prominence of fatigue loads. Many studies attempted to reduce fatigue loads while generating sufficient power by dynamically controlling the blade pitch [7,[13][14][15][16][17][18]. Yet, additional restraints that aerodynamicist had and still have to consider are the public acceptance mainly from the generated noise by the wind turbine.…”

Wind turbine pitch optimization

“…with variables p(θ) ∈ R 3 for θ ∈ [0, 3 ]. In the model given by equations (1)- (4), τ x only depends on p(θ) through the lift and drag coefficients C l (α) and C d (α), an example of which are illustrated in figure 4 [8].…”

“…These costs are significant, and dramatically impact the profitability of the turbine. Many studies [1], [2], [3], [4], [5] have been performed which attempt to reduce fatigue loads while also generating sufficient power by dynamically controlling blade pitching. In this paper, we present a general blade pitching approach for fatigue load minimization based on convex optimization.…”

Optimal LQG Controller for Variable Speed Wind Turbine Based on Genetic Algorithms

“…That type of control shows useful properties of good performance and robustness in controller design applied to wind energy converters system [1]. Although the application of LQG control for DFIG wind turbines is not new, recent research report using LQG controllers successfully [2,3,4,5].…”