Rated Wind Conditions Research Articles

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

AbstractRain‐induced leading‐edge erosion (LEE) of wind turbine blades (WTBs) is associated with high repair and maintenance costs. The effects of LEE can be triggered in less than 1 to 2 years for some wind turbine sites, whereas it may take several years for others. In addition, the growth of erosion may also differ for different blades and turbines operating at the same site. Hence, LEE is a site‐ and turbine‐specific problem. In this paper, we propose a probabilistic long‐term framework for assessing site‐specific lifetime of a WTB coating system. Case studies are presented for 1.5 and 10 MW wind turbines, where geographic bubble charts for the leading‐edge lifetime and number of repairs expected over the blade's service life are established for 31 sites in the Netherlands. The proposed framework efficiently captures the effects of spatial and orographic features of the sites and wind turbine specifications on LEE calculations. For instance, the erosion is highest at the coastal sites and for sites located at higher altitudes. In addition, erosion is faster for turbines associated with higher tip speeds, and the effects are critical for such sites where the exceedance probability for rated wind conditions are high. The study will aid in the development of efficient operation and maintenance strategies for wind farms.

Downwind pre‐aligned rotors for extreme‐scale wind turbines

AbstractDownwind force angles are small for current turbines systems (1–5 MW) such that they may be readily accommodated by conventional upwind configurations. However, analysis indicates that extreme‐scale systems (10–20 MW) will have larger angles that may benefit from downwind‐aligned configurations. To examine potential rotor mass reduction, the pre‐alignment concept was investigated a two‐bladed configuration by keeping the structural and aerodynamic characteristics of each blade fixed (to avoids a complete blade re‐design). Simulations for a 13.2 MW rated rotor at steady‐state conditions show that this concept‐level two‐bladed design may yield 25% rotor mass savings while also reducing average blade stress over all wind speeds. These results employed a pre‐alignment on the basis of a wind speed of 1.25 times the rated wind speed. The downwind pre‐aligned concept may also reduce damage equivalent loads on the blades by 60% for steady rated wind conditions. Even higher mass and damage equivalent load savings (relative to conventional upwind designs) may be possible for larger systems (15–20 MW) for which load‐alignment angles become even larger. However, much more work is needed to determine whether this concept can be translated into a practical design that must meet a wide myriad of other criteria. Copyright © 2017 John Wiley & Sons, Ltd.

Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization

The problem of designing a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed. The objective is to operate the wind turbines in order to have maximum wind power extraction while also the mechanical loads are reduced. Two control strategies were proposed seeking a better performance. The first strategy uses a tracking controller that ensures the optimal angular velocity for the rotor. The second strategy uses a Maximum Power Point Tracking (MPPT) algorithm while a non-homogeneous quasi-continuous high-order sliding mode controller is applied to ensure the power tracking. Two algorithms were developed to solve the tracking control problem for the first strategy. The first one is a sliding mode output feedback torque controller combined with a wind speed estimator. The second algorithm is a quasi-continuous high-order sliding mode controller to ensure the speed tracking. The proposed controllers are compared with existing control strategies and their performance is validated using a FAST model based on the Controls Advanced Research Turbine (CART). The controllers show a good performance in terms of energy extraction and load reduction.

$\ell_{1}$-Optimal Control of Large Wind Turbines

We present an l1-control scheme for multivariable pitch control in full load region. Two decoupled linear time-invariant models are derived using Coleman transformation and gain scheduling to design collective and individual pitch controllers independently. Individual pitch control is used to decrease the blade root bending moment. A new l1-control setup for collective pitch control taking into account the collective bending moment in Coleman mode is presented. This further decreases the blade root bending moment while rotor speed is maintained constant above rated wind conditions. Simulations with a full nonlinear aeroelastic model over the whole load region show the applicability of the proposed control strategy and lifetime weighted damage equivalent loads are computed. Compared to classical collective and individual pitch control, a significant load reduction is achieved without losses in energy production.

Model predictive control of a wind turbine using short‐term wind field predictions

ABSTRACTAs wind turbines become larger and hence more flexible, the design of advanced controllers to mitigate fatigue damage and optimise power capture is becoming increasingly important. The majority of the existing literature focuses on feedback controllers that use measurements from the turbine itself and possibly an estimate or measurement of the current local wind profile. This work investigates a predictive controller that can use short‐term predictions about the approaching wind field to improve performance by compensating for measurement and actuation delays.Simulations are carried out using the FAST aeroelastic design code modelling the NREL 5 MW reference turbine, and controllers are designed for both above rated and below rated wind conditions using model predictive control. Tests are conducted in various wind conditions and with different future wind information available. It is shown that in above rated wind conditions, significant fatigue load reductions are possible compared with a controller that knows only the current wind profile. However, this is very much dependent on the speed of the pitch actuator response and the wind conditions. In below rated wind conditions, the goals of power capture and fatigue load control were considered separately. It was found that power capture could only be improved using wind predictions if the wind speed changed rapidly during the simulation and that fatigue loads were not consistently reduced when wind predictions were available, indicating that wind predictions are of limited benefit in below rated wind conditions. Copyright © 2012 John Wiley & Sons, Ltd.

Structural capacity and the 20 MW wind turbine

This article addresses a generic and fundamental question: given the specification for a structure, how can one assess or even express its capacity without first designing it? The question is motivated by the consideration of how wind turbines (offshore wind turbines in particular) may scale up further. An underlying premise is that the wind-turbine designs that have evolved from 50 kW to 5 MW may warrant re-examination to check whether scaling effects demand new approaches at larger scales. Since several in the industry are already setting sights on 8 MW and even 10 MW machines as extrapolations of current designs, this article considers the development of a 20 MW (232 m diameter) machine. The conventional three-bladed arrangement on a slender tower is examined for notional 5 and 20 MW machines for similar rated wind conditions. Initially, the article considers the structural capacity requirements for conventional designs at both 5 and 20 MW and how these can be reduced substantially – using a floating framework in place of a tower and by deploying cable bracing on the rotor. When tower bending and the non-productive blade bending moments have thus been addressed, the turbine torque itself emerges as a major cause of cost. The turbine torque directly influences the costs of blades, pitch and yaw bearings, direct-drive generators (if present), gearbox (if present), and main shaft, and it is confirmed that in all cases, the total amounts of material required are at least proportional to the turbine torque for conventional designs. An alternative wind-turbine configuration is examined. In this, gravity is co-opted as an ally rather than an enemy, and power conversion takes place entirely within the rotor by allowing gravity to move bodies within the rotor. The concept is illustrated for a 20 MW machine and shown to be entirely workable in principle. A strong feature of this proposed new machine configuration is that the costs are almost exclusively structural and can be quantified in terms of the uniform currency of structural capacity. The scalability of this concept becomes clear by observing that the mean velocities of the moveable masses relative to the main rotor structure are virtually independent of machine scale.

Simulating Feedback Linearization control of wind turbines using high‐order models

AbstractAs wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.

Individual Blade Pitch Control for the Controls Advanced Research Turbine (CART)

Pitching the individual blades of a horizontal-axis wind turbine allows control of asymmetric aerodynamic loads, which in turn influences structural loads in the nonrotating frame such as tower side-side bending. These loads are not easily controlled by traditional collective pitch algorithms. This paper presents the design of individual pitch control systems for implementation on the Controls Advanced Research Turbine (CART) in Colorado to verify controller performance for load attenuation. The control designs are based on linear time-periodic state-space models of the turbine and use optimal control methods for gain calculation. Comparisons are made between new individual pitch, new collective pitch, and baseline controller performance in both above rated and below rated wind conditions. Results from simulations show the potential of individual pitch to reduce tower side-side fatigue damage in above rated wind speeds (by 70% compared to baseline control) but with no improvement over collective pitch in below rated wind speeds. Fatigue load reductions in tower fore-aft, shaft torsion, and blade flap are also observed. From 13h of field testing, both collective and individual pitch controllers achieve a reduction in fatigue damage. However, the superior performance of individual pitch control observed in simulation was not verified by the field test results.