Smart Rotor Research Articles

Active alleviation of fatigue stress on blades by adaptively maneuvered deformable trailing edge flaps (DTEF).

The concept of "smart rotor" is an evolving advancement in wind turbine which enables an intelligent active flow control in rotor. The deformable trailing edge flap (DTEF) is a part of smart rotor concept which implements a customized active load control. The trailing edge flap actuator effectively replaces the tedious blade pitch actuation and conserves the actuation energy required for pitching the entire blade. The DTEFs require a fast computing, anticipatory controller for optimally tuning the flap angle with minimal power compromise. This work analyzes the performance of advanced control strategies like model predictive control (MPC), adaptive MRAC control, and DQ controllers. The MRAC controller is found to reduce the fatigue stress by 40% and the MPC controller damps up to 70% more efficiently than the typical feedback controller. The control strategies are aided by the LiDAR-based preview wind data for the active manipulation of trailing edge flap angle control. The validation of proposed controller is done using power analysis curve and the component fatigue lifetime analysis using MLIFE software. The above analyses are done in NREL Onshore 5-MW FAST wind turbine model which could be interfaced with MATLAB with modified AeroDyn code for active flap deflection.

Recent technology and challenges of wind energy generation: A review

Energy is an integral part of economic growth and social development. Renewable energy sources are naturally occurring, which can help in reducing the dependency on non-renewable resources. The increasing effects of climate change have led to the utilization of renewable energy resources for power generation, among which wind is one of the significant sources of power generation. It provides a reliable, sustainable, and environmentally friendly alternative contributing to national energy security in the current age of decreasing global reserves of non-renewable resources across the globe. This paper reviews the wind energy technologies used, mainly focusing on the types of turbines used and their future scope. Further, the paper briefly discusses certain future wind generation technologies, namely airborne, offshore, smart rotors, multi-rotors, and other small wind turbine technologies. It also briefly discusses ways to improve the efficiency of different turbine generation technologies, majorly non-conventional ideas of wind turbine technologies based on cross axis wind turbine (CAWT), vertical axis wind turbine (VAWT), magnetic-based wind turbine. Overall, the summarization of wind energy here consists of four aspects: (1) wind turbine structure, (2) wind power generation technologies, (3) wind energy assessment methodologies, (4) limitation of developed technologies and future scope of wind energy development.

Parameter varying control of wind turbine smart rotor for structural load mitigation

This study investigates the Linear Parameter Varying (LPV) control of a Horizontal Axis Wind Turbine (HAWT) smart rotor in order to alleviate the structural loads. The smart rotor blades are equipped with actuators called Deformable Trailing Edge Flap (DTEF). These flaps benefit from a continuous airfoil deformation on the trailing edge in order to change the aerodynamic properties of blades. The objective of using a flap is to reduce the amplitude of load fluctuations in high wind speeds to decrease the fatigue loads on the wind turbine components and increase their working life. Here, the aerodynamic behavior of NACA 64-418 airfoil in the presence of DTEF deflection is studied numerically. The airfoil with 10% chord deformation is mounted on 5 MW NREL reference wind turbine blades in 67% to 95% of its length relative to the blade root. The nonlinear aeroelastic FAST code is used to determine the effects of DTEFs on structural load mitigation. Consequently, the modeling of nonlinear wind turbine system using LPV approach is discussed including the angle of DTEFs as a control input. A robust LPV controller has been designed using Linear Matrix Inequality (LMI) solution along the operating trajectory to guarantee the internal stability and H∞ robust performance of the closed-loop system in the presence of modeling uncertainties as well as wind turbulence. In sum, the idea of this study is the aerodynamic modeling of the wind turbine equipped with a smart rotor, designing an LPV controller and comparing the results with the conventional PI gain-scheduled controller. The principal objective is to reduce the amplitude of blade root flapwise bending moment oscillations about its mean values along the operating trajectory. As a summary of the results, a reduction in blade root flapwise bending moment fatigue load has been observed by 33% based on Damage Equivalent Load (DEL) calculation.

Nonlinear modelling and adaptive control of smart rotor wind turbines

This paper develops a nonlinear mid-fidelity aeroservoelastic model for smart rotor wind turbines and studies the turbulent load alleviation of the wind turbines with trailing edge flaps (TEFs) actuated by a novel proportional-derivative model-free adaptive control (PD-MFAC) algorithm. This nonlinear model contains a structural model for the tower and blades represented by geometrically non-linear composite beams and an aerodynamic model for the rotor using a vortex panel method coupled with a stall delay process. The capability of the new aerodynamic model to deal with flow separations and analyze the detailed flow field enables it to simulate the dynamic response of the wind turbine blade sections with TEFs with arbitrary size and deflection angles. It is shown that the TEF alters the aerodynamic coefficients in a complex manner which could be explained by the evolution of the detailed vortical field. Furthermore, three independent PD-MFAC TEF controllers are designed to alleviate the turbulent load acting on the wind turbines. The effectiveness of the controller in terms of turbulent load alleviation is evaluated by the root mean square value of the blade root-bending moment (RBM). A traditional Gain-scheduled PI (GS-PI) controller is also designed as a comparison to the PD-MFAC controller. Simulation results show that to reduce the RBM and blade tip deflection (BTD) caused by external disturbances, the PD-MFAC flap controller shows more effective performance than the GS-PI flap controllers.

Smart Variable Rotor of Vertical Axis Wind Turbine with Faster Cut-in Speed and Wide Range Extract Power Using Artificial Intelligent

This paper presents the standalone type vertical axis wind turbine (VAWT) smart rotor using variable diameter rotor (VDR) in order to tap constant power and maintain cut-in wind speed. VDR is a smart variable rotor capable of operating at a low wind speed, in which the width of diameter rotor is adjustable using actuators. The VDR rotor is connected to the permanent magnet synchronous generator (PMSG) and a DC-DC boost converter. The controller of VDR rotors uses fuzzy logic controller (FLC). The FLC variable inputs are wind speed data and power output, broken down into cluster groups to determine the diameter rotor position. The wind speed data as fuzzy input are produced by wind speed estimator using artificial neural network (ANN) to maintain cut-in speed to be faster. The velocity movement of VDR is limited from 75 cm to 150 cm. The VDR extension increases by 25% when the wind speed decreases from 8 to 6 m/s to obtain consistent power at 150 Watt. The experimental of VDR system is tested at low wind speeds ranging from 1 to 8 m/s as a verification of the control system. The result showed that the VDR produced five times increase in efficiency with faster cut-in wind speed at 2.0 m/s.

CFD Studies of Wake Characteristics and Power Capture of Wind Turbines With Trailing Edge Flaps

Trailing edge flap (TEF) devices will change downstream wake development in wind farms comprising smart rotors, which in turn affect the performance of downstream wind turbines. To study the influence of TEFs on downstream wake development and power capture of wind turbines in wind farms, computational fluid dynamics (CFD) simulations using the three-dimensional rotor model are performed in this paper. The CFD software Fluent is adopted to simulate a wind farm with two tandem wind turbines with TEFs at rated and below rated turbulent wind conditions. Under the 11.4 m/s turbulent wind conditions, the results show that the deflection of the TEF increases the velocity deficit and reduces the wake width, making the wake more complicated. And the positive TEF angle has a greater influence on downstream wake than the negative TEF angle. Additionally, under the 9 m/s turbulent wind conditions, the total power of the two wind turbines increases by 6.5% when the TEF angles are 6°.

Load control of floating wind turbine on a Tension-Leg-Platform subject to extreme wind condition

This paper mainly focuses on the control of a typical extreme load, i.e. Extreme Coherent Gust with Direction Change (ECD) and Normal Sea State (NSS), on a floating wind turbine (FWT) with a Tension-Leg-Platform (TLP), following the International Electro-technical Commission (IEC) standard. Using an integrated aero-hydro-servo-elastic code, the control action was implemented through the local perturbations of the Deformable Trailing Edge Flaps (DTEFs) on the blade surfaces and thus to the whole FWT. Investigations were separately conducted in four phases, depending on the complex yaw or/and pitching functions of the turbine. It was found that although the uncontrolled extreme loads on the FWT, which mainly originated from the combined influences of ECD and NSS, were rather strong, the smart rotor control very effectively reduced the standard deviations in the primary fluctuating loads on the blades, driving-chain components, tower and TLP by up to 10–35%. The good control performance lay in the altered flow-blade interactions from in-phased to anti-phased situations at dominant mode frequencies, thus significantly impairing their coherences, and subsequently the loads on the blades and other interrelated elements of the turbine system.

Smart Rotor With Trailing Edge Flap Considering Bend–Twist Coupling and Aerodynamic Damping: Modeling and Control

Aerodynamic damping and bend–twist coupling significantly affect the dynamic response of wind turbines. In this paper, unsteady aerodynamics, aerodynamic damping, and bend–twist coupling (twist-towards-feather) are combined to establish a smart rotor model with trailing edge flaps (TEFs) based on a National Renewable Energy Laboratory (NREL) 5 MW reference horizontal-axis wind turbine. The overall idea is to quantitatively evaluate the influence of aerodynamic damping and bend–twist coupling on the smart rotor and to present the control effect of the TEFs under normal wind turbine operating conditions. An aerodynamic model considering the dynamic stall and aerodynamic damping as well as a structural bend–twist coupling model with the influence of gravity and centrifugal force are incorporated into the coupling analysis. The model verification shows that the present model is relatively stable under highly unsteady wind conditions. Then, a robust adaptive tracking (RAT) controller is designed to suppress fluctuations in both the flapwise tip deflection and output power. The simulations show an average reduction of up to 63.86% in the flapwise tip deflection power spectral density (PSD) of blade 1 at the 1P frequency, with an average reduction in the standard deviation of the output power of up to 34.33%.

Smart control of fatigue loads on a floating wind turbine with a tension-leg-platform

In this paper, the smart fatigue load control of a representative floating wind turbine (FWT) with a tension-leg-platform was numerically investigated using our newly integrated aero-hydro-servo-elastic code. The control was achieved by introducing a local, fast and efficient closed-loop system based on deformable trailing edge flap (DTEF) activation near the tip of each blade, and as a result, it was able to effectively suppress the unstable loads on the critical components, as well as improve the general performances of FWT. The control effectiveness lies in the great impairment of original synchronized wind-rotor relationship by controllable DTEFs. This significantly decreased the combined effects of wind, waves and primary modes of blade, driving-chain components, tower and TLP platform, and subsequently attenuated the main fatigue loads on them. The effect of the control mechanism became more drastic as the investigation focused on the case beyond the rated wind velocity. In addition, the research findings showed the crucial role that the wind-wave-rotor relationship played during the development of smart rotor controller.

Optimize Rotating Wind Energy Rotor Blades Using the Adjoint Approach

Wind energy rotor blades are highly complex structures, both combining a large aerodynamic efficiency and a robust structure for lifetimes up to 25 years and more. Current research deals with smart rotor blades, improved for turbulent wind fields, less maintenance and low wind sites. In this work, an optimization tool for rotor blades using bend-twist-coupling is developed and tested. The adjoint approach allows computation of gradients based on the flow field at comparably low cost. A suitable projection method from the large design space of one gradient per numerical grid cell to a suitable design space for rotor blades is derived. The adjoint solver in OpenFOAM is extended for external flow. As novelty, we included rotation via the multiple reference frame method, both for the flow and the adjoint field. This optimization tool is tested for the NREL Phase VI turbine, optimizing the thrust by twisting of various outer parts between 20–50% of the blade length.

Optimization of sizing parameters and multi-objective control of trailing edge flaps on a smart rotor

Abstract In this study, a wind turbine model with a smart rotor is presented to optimize the sizing parameters of the trailing edge flap (TEF) and design the multi-objective TEF controller. The proposed model consists of TEF actuators, and the aerodynamic, applied load, structural, drive chain, and generator models. Additionally, under standard wind turbine control, the present model shows good agreements with FAST at different wind conditions. At the rated steady wind condition, the TEFs yield exactly the same effects as those elicited by FAST. An approach is proposed using two orthogonal experiments to optimize the TEF sizing parameters for maximizing the TEF effects on blade load alleviation and wind turbine output power smoothness. As a result, a group of optimal TEF sizing parameters is obtained. A multi-objective TEF controller adopting multivariable dynamic matrix control (M–DMC) and nonlinear dynamic matrix control (N–DMC) is used to control the flapwise blade root moment and output power. The simulations indicate that the average reduction rates of the flapwise root moment power spectral density (PSD) of blade 1 are within the range of 87–97% at 1 P frequency, and that the average reduction rate of the generator power standard deviation is within the range of 8–42%.

Sensitivity analysis of smart rotor under to uncertainties

This contribution encompasses the sensitivity analysis of flexible rotor with active vibration control subjected to uncertainties. The uncertain parameters consist of small variations that are modeled by using random variables and random fields. The structure response subjected to uncertain parameters is analyzed based on the stochastic modeling. Numerical simulations illustrate the structural response of the rotor and their sensitivity indices.

Smart Rotors: Dynamic-Stall Load Control by Means of an Actuated Flap

This study focuses on an active strategy for unsteady-load control by means of a trailing-edge flap. Experiments on a 2D pitching and heaving NACA 0018 airfoil with an actuated trailing-edge flap are performed at a reduced frequency in a free-stream flow with . The model is equipped with 24 differential pressure transducers to provide with the time-resolved distribution of the pressure difference between pressure and suction sides. Results show that an actuated flap significantly decreases the magnitude of unsteady loads. A reduced order model of the flap effect on the loads is proposed. The loads are estimated by adding the contribution of the clean wing with the flap one. This model can be applied to unsteady loads for both attached flow and dynamic stall conditions, constituting an effective control strategy for dynamic loads, if the airfoil transition location is properly controlled.

On Advanced Control Methods toward Power Capture and Load Mitigation in Wind Turbines

Abstract This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying turbulent wind fields have been under extensive investigation in recent years. We divide the related research activities into three categories: modeling and dynamics of wind turbines, active control of wind turbines, and passive control of wind turbines. Regarding turbine dynamics, we discuss the physical fundamentals and present the aeroelastic analysis tools. Regarding active control, we review pitch control, torque control, and yaw control strategies encompassing mathematical formulations as well as their applications toward different objectives. Our survey mostly focuses on blade pitch control, which is considered one of the key elements in facilitating load reduction while maintaining power capture performance. Regarding passive control, we review techniques such as tuned mass dampers, smart rotors, and microtabs. Possible future directions are suggested.

Numerical investigation of azimuth dependent smart rotor control on a large-scale offshore wind turbine

The smart fatigue load control of a large-scale wind turbine blade was numerically investigated on our newly integrated aero-servo-elastic platform with emphasis on the effect of azimuth angles. It was found that the smart control effectively reversed the phases of the flapwise aerodynamic force or the acceleration through the controllable deformable trailing edge flap (DTEF) activation within most of rotor azimuth angle range, turning in-phased flow-blade interaction into an anti-phased one at primary 1P mode, significantly enhancing the damping of the fluid-structure system and subsequently contributing to the greatly attenuatedflapwise fatigue loads on the blade and turbine performances. This aero-elastic control physics was most drastic as the investigations were focused on the case beyond the rated wind velocity, leading to the maximum reduction percentages in the time-averaged and azimuth-averaged fatigue loads up to about 30.0%, in contrast to the collective pitch control method. In addition, the finding pointed to a crucial role that the suppression of the coupled flow-blade system dependent on azimuth angles played in the smart blade control, which might guarantee better effectiveness if it would be considered in the development of the DTEF controller.

High‐fidelity linear time‐invariant model of a smart rotor with adaptive trailing edge flaps

AbstractA high‐fidelity linear time‐invariant model of the aero‐servo‐elastic response of a wind turbine with trailing‐edge flaps is presented and used for systematic tuning of an individual flap controller. The model includes the quasi‐steady aerodynamic effects of trailing‐edge flaps on wind turbine blades and is integrated in the linear aeroelastic code HAWCStab2. The dynamic response predicted by the linear model is validated against non‐linear simulations, and the quasi‐steady assumption does not cause any significant response bias for flap deflection with frequencies up to 2–3 Hz. The linear aero‐servo‐elastic model support the design, systematic tuning and model synthesis of smart rotor control systems. As an example application, the gains of an individual flap controller are tuned using the Ziegler–Nichols method for the full‐order poles. The flap controller is based on feedback of inverse Coleman transformed and low‐pass filtered flapwise blade root moments to the cyclic flap angles through two proportional‐integral controllers. The load alleviation potential of the active flap control, anticipated by the frequency response of the linear closed‐loop model, is also confirmed by non‐linear time simulations. The simulations report reductions of lifetime fatigue damage up to 17% at the blade root and up to 4% at the tower bottom. Copyright © 2016 John Wiley & Sons, Ltd.

Fatigue and extreme load reduction of wind turbine components using smart rotors

In this paper the reductions of fatigue and extreme loads of wind turbine components are analysed. An individual flap controller was designed to reduce cyclic loads. The load reduction potential was computed for power production and start-up load cases with normal and extreme turbulence, extreme gust events, and direction changes according to the certification specifications. Additional to the highly investigated reduction of the blade root fatigue damage equivalent load, also significant reductions could be shown for both shaft and tower loads. When applying smart rotors, most components experience a fatigue load reduction of 5–15%, with the exception of the flapwise blade root moment, which is decreased by 23.8% and the blade root torsional moment which increases 14%. For the simulated ultimate loads, the flapwise root bending moment is reduced by 8%, while tip deflections get reduced by 6%. The most significant extreme load reduction can be found for loads in the tower that relate to asymmetry of the inflow, namely tower torsion and the fore-aft moment at the tower top. The blade root torsional moment is increased significantly. The changes in the ultimate load of all other components remain below 2%.

Smart fatigue load control on the large-scale wind turbine blades using different sensing signals

This paper presented a numerical study on the smart fatigue load control of a large-scale wind turbine blade. Three typical control strategies, with sensing signals from flapwise acceleration, root moment and tip deflection of the blade, respectively, were mainly investigated on our newly developed aero-servo-elastic platform. It was observed that the smart control greatly modified in-phased flow-blade interaction into an anti-phased one at primary 1P mode, significantly enhancing the damping of the fluid-structure system and subsequently contributing to effectively attenuated fatigue loads on the blade, drive-chain components and tower. The aero-elastic physics behind the strategy based on the flapwise root moment, with stronger dominant load information and higher signal-to-noise ratio, was more drastic, and thus outperformed the other two strategies, leading to the maximum reduction percentages of the fatigue load within a range of 12.0–22.5%, in contrast to the collective pitch control method. The finding pointed to a crucial role the sensing signal played in the smart blade control. In addition, the performances within region III were much better than those within region II, exhibiting the benefit of the smart rotor control since most of the fatigue damage was believed to be accumulated beyond the rated wind speed.

Optimizing Wind Turbine Efficiency by Deformable Structures in Smart Blades

This paper presents a method for optimizing blade designs in smart rotors; the objective is to maximize power regardless of wind conditions. An extensive analysis of what is known as “smart blades,” from aeronautical solutions and helicopter rotors is provided. Moreover, trends in computational and experimental research are analyzed, an assessment and categorization of the options available for aerodynamic control surfaces are made. The study and analysis of its main components such as sensors, mechanisms of actuation, and materials are included. Advance research in this technology is presented as a potential solution for more efficient blade designs, and methods for reducing aerodynamic loads are discussed.

Iterative learning control applied to a non-linear vortex panel model for improved aerodynamic load performance of wind turbines with smart rotors

The inclusion of smart devices in wind turbine rotor blades could, in conjunction with collective and individual pitch control, improve the aerodynamic performance of the rotors. This is currently an active area of research with the primary objective of reducing the fatigue loads but mitigating the effects of extreme loads is also of interest. The aerodynamic loads on a wind turbine blade contain periodic and non-periodic components and one approach is to consider the application of iterative learning control algorithms. In this paper, the control design is based on a simple, in relative terms, computational fluid dynamics model that uses non-linear wake effects to represent flow past an airfoil. A representation for the actuator dynamics is included to undertake a detailed investigation into the level of control possible and on how performance can be effectively measured.