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1.
Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads. The method allows accommodating unknown disturbance effects by using the combination of disturbance observers and disturbance rejection controllers. The actual main problem of DAC is to define suitable disturbance observer and controller gain matrices to achieve the desired overall performance including turbine speed regulation in combination with structural load mitigation. The disturbance rejection controller is often designed and tuned separately for individual applications and operating conditions. The closed-loop system stability and uncertainties due to the use of the linearized reduced-order model in controller synthesis procedure are not fully considered. This paper introduces a method to design DAC by optimizing the observer and controller parameters simultaneously to guarantee system performance respecting to structural loads mitigation, power regulation, and robustness. To eliminate the rotor speed control steady-state error due to model uncertainties, partial integral action is included. Simulation results using NREL reference wind turbine models show that the proposed method successfully regulates the rotor speed without error despite the presence of the model uncertainties. Structural loads are also reduced using proposed method compared to DAC designed by Kronecker product method. The proposed approach is able to define a stable and robust DAC controller by solving a non-smooth H∞ optimization problem with structure and stability constraints. 相似文献
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Over the past few decades, global demand for renewable energy has been rising steadily. To meet this demand, there has been an exponential growth in size of wind turbines (WTs) to capture more energy from wind. Consequent increase in weight and flexibility of WT components has led to increased structural loading, affecting reliability of these wind energy conversion systems. Spatio-temporal variation of rotor effective wind field acts as a disturbance to a WT system, hence, necessitating controllers that can cancel this disturbance. Additionally, assumptions made in extracting linear models for controller design lead to modeling errors resulting from changing operating conditions. Previous attempts have proposed robust controllers incorporating wind disturbance models. However, these controllers have been evaluated on smaller WTs, which experience lower structural loading than larger ones. Additionally, a majority these controllers are based on collective pitch control (CPC), hence do not address loading in the blades. To address these challenges, this contribution proposes an independent pitch-based robust disturbance accommodating controller (IPC-RDAC) for reducing structural loads and regulating generator speed in utility-scale WTs. The proposed controller is designed using
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As 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. 相似文献
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大型风电机组独立变桨控制技术研究 总被引：4，自引：0，他引：4
通过对风力机简化模型的分析,推导出风力机的运动方程和输出方程;通过卡尔曼坐标变换将塔架前后运动方程和载荷输出方程所代表的线性时变系统解耦为线性时不变系统,在此基础上提出带3个独立控制环的独立变桨控制策略;利用"GH Bladed"软件对独立变桨控制策略进行仿真试验研究,仿真试验结果表明,采用独立变桨控制技术不但能实现转速控制功能,还能有效减小叶片根部挥舞力矩、轮毂倾翻力矩、偏航力矩的波动,从而能有效降低变桨轴承、主轴、轮毂、偏航轴承、塔架上的疲劳载荷。 相似文献
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David Stockhouse;Manuel Pusch;Rick Damiani;Senu Sirnivas;Lucy Pao; 《风能》2024,27(11):1205-1228
A principal challenge facing the control of floating offshore wind turbines (FOWTs) is the problem of instability, or “negative damping,” when using blade pitch feedback to control generator speed. This closed-loop instability can be attributed to non-minimum phase zeros in the transfer function from blade pitch to generator speed. Standard approaches to improving stability and performance include robust tuning of control gains and introducing multiple feedback loops to respond to platform motion. Combining these approaches is nontrivial because multiple control loops complicate the impact of coupling in the system dynamics. The single-loop approach to analyzing stability robustness neglects inter-loop coupling, while a simplistic multi-loop approach is highly sensitive to dimensional scaling and overestimates the robustness of the single-loop controller. This work proposes a sensitivity representation that separates some of the natural FOWT dynamic coupling into a parallel feedback loop in the sensitivity function loop to address both of these concerns. The modified robustness measure is used with a simplified linear FOWT model to optimize scheduled multi-loop control parameters in an automated tuning procedure. This controller is implemented for the 10-MW Ultraflexible Smart FLoating Offshore Wind Turbine (USFLOWT) and compared against conventional single- and multi-loop controllers tuned using frequency-domain analysis and high-fidelity OpenFAST simulations. The multi-loop robust controller shows the highest overall performance in generator speed regulation and tower load reduction, though consideration of power quality, actuator usage, and other structural loading leads to additional trade-offs. 相似文献
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E. A. Bossanyi 《风能》2003,6(2):119-128
If a pitch‐regulated wind turbine has individual pitch actuators for each blade, the possibility arises to send different pitch angle demands to each blade. The possibility of using this as a way of reducing loads has been suggested many times over the years, but the idea has yet to gain full commercial acceptance. There are a number of reasons why this situation may be set to change, and very significant load reductions can result. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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This article deals with nonlinear model‐based control design for wind turbines. By systematically integrating several mechanical degrees of freedom in the control design model, the load mitigation potential from the proposed multivariable control framework is demonstrated. The application of the linear matrix inequality (LMI)‐based control design is discussed in detail. Apart from the commonly considered power production mode, an extended operating range to provide stabilization of the electrical grid through power tracking is considered. This control functionality allows for an evaluation of the resulting fatigue and ultimate loads for power tracking at different dynamic requirements. The results indicate that under the impact of a dedicated control scheme, this functionality is feasible with respect to the occurring loads and operational behavior of the wind turbine. 相似文献
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LIDAR systems are able to provide preview information of wind disturbances at various distances in front of wind turbines. This technology paves the way for new control concepts in wind energy such as feedforward control and model predictive control. This paper compares a nonlinear model predictive controller with a baseline controller, showing the advantages of using the wind predictions in the optimization problem to reduce wind turbine extreme and fatigue loads on tower and blades as well as to limit the pitch rates. The wind information is obtained by a detailed simulation of a LIDAR system. The controller design is evaluated and tested in a simulation environment with coherent gusts and a set of turbulent wind fields using a detailed aeroelastic model of the wind turbine over the full operation region. Results show promising load reduction up to 50% for extreme gusts and 30% for lifetime fatigue loads without negative impact on overall energy production. This controller can be considered as an upper bound for other LIDAR assisted controllers that are more suited for real time applications. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Offshore wind turbines suffer from asymmetrical loading (blades, tower, etc), leading to enhanced structural fatigue. As well as asymmetrical loading different faults (pitch system faults etc.) can occur simultaneously, causing degradation of load mitigation performance. Individual pitch control (IPC) can achieve rotor asymmetric loads mitigation, but this is accompanied by an enhancement of pitch movements leading to the increased possibility of pitch system faults, which exerts negative effects on the IPC performance. The combined effects of asymmetrical blade and tower bending together with pitch sensor faults are considered as a “co‐design” problem to minimize performance deterioration and enhance wind turbine sustainability. The essential concept is to attempt to account for all the “fault effects” in the rotor and tower systems, which can weaken the load reduction performance through IPC. Pitch sensor faults are compensated by the proposed fault‐tolerant control (FTC) strategy to attenuate the fault effects acting in the control system. The work thus constitutes a combination of IPC‐based load mitigation and FTC acting at the pitch system level. A linear quadratic regulator (LQR)‐based IPC strategy for simultaneous blade and tower loading mitigation is proposed in which the robust fault estimation is achieved using an unknown input observer (UIO), considering four different pitch sensor faults. The analysis of the combined UIO‐based FTC scheme with the LQR‐based IPC is shown to verify the robustness and effectiveness of these two systems acting together and separately. 相似文献
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Jennifer Annoni Pieter M. O. Gebraad Andrew K. Scholbrock Paul A. Fleming Jan‐Willem van Wingerden 《风能》2016,19(6):1135-1150
Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial‐induction‐based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high‐order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial‐induction‐based control shown in the high‐order model. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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To achieve load reduction and power optimization, wind turbine controllers design requires the availability of reliable control‐oriented linear models. These are needed for model‐based controller design. Model identification of wind turbine while operating in closed loop is an appropriate solution that has recently shown its capabilities when linear time‐invariant controllers and complicated control structures are present. However, the collective pitch control loop, one of the most important wind turbine loops, uses non‐linear controllers. Typically, this non‐linear controller is a combination of a linear controller and a gain scheduling. This paper presents a new algorithm for identification in closed‐loop operation that allows the use of this kind of non‐linear controllers. The algorithm is applied for identification the collective pitch demand to generator speed of a wind turbine at various operating points. The obtained models are presented and discussed from a control point of view. The validity of these models is illustrated by their use for the design of a linear fix robust controller. The performance based on simulation data of this linear controller is similar to that obtained with simulations based on a linear controller with gain scheduling, but its design and implementation is much simpler. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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风力机大型化已成为风电技术发展的主要趋势。但随之而来的叶片尺寸增大、气弹特性增强、多尺度流动等问题将导致叶片处于更加复杂严峻的风况及载荷环境。为提高叶片应对复杂风况及载荷的能力,提高叶片气动效率,有必要采用先进有效的流动控制技术以满足叶片气动降载与流动分离控制的需求。针对当前主流的流动控制技术进行了介绍,并对较具发展潜力的尾缘襟翼与自适应襟翼研究现状进行了重点介绍。现阶段流动控制技术并未在风力机叶片中得到广泛应用,一方面在于流动控制技术尚难与叶片现有主体控制技术相结合,以达到相辅相成的控制效果;另一方面在于对于部分控制技术,如自适应襟翼等,其控制特点尤其是其在风力机实际运行中的控制特点尚不明确。后续研究中,对于叶片气动降载,应结合更为先进的控制方法与更可靠的研究手段开展尾缘襟翼控制与叶片主体控制的协同控制研究;对于流动分离控制技术,应侧重于改善被动控制技术在非适用工况下的不良影响,同时开展流动控制技术在整机中的实验与数值研究,加快流动分离控制技术的实际应用。 相似文献
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Structural loads of wind turbines are becoming critical because of the growing size of wind turbines in combination with the required dynamic output demands. Wind turbine tower and blades are therefore affected by structural loads. To mitigate the loads while maintaining other desired conditions such as the optimization of power generated or the regulation of rotor speed, advanced control schemes have been developed during the last decade. However, conflict and trade‐off between structural load reduction capacity of the controllers and other goals arise; when trying to reduce the structural loads, the power production or regulation performance may be also reduced. Suitable measures are needed when designing controllers to evaluate the control performance with respect to the conflicting control goals. Existing measures for structural loads only consider the loads without referring to the relationship between loads and other control performance aspects. In this contribution, the conflicts are clearly defined and expressed to evaluate the effectiveness of control methods by introducing novel measures. New measures considering structural loads, power production, and regulation to prove the control performance and to formulate criteria for controller design are proposed. The proposed measures allow graphical illustration and numerical criteria describing conflicting control goals and the relationship between goals. Two control approaches for wind turbines, PI and observer‐based state feedback, are defined and used to illustrate and to compare the newly introduced measures. The results are obtained by simulation using Fatigue, Aerodynamics, Structures, and Turbulence (FAST) tool, developed by the National Renewable Energy Laboratory (NREL), USA. 相似文献
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The non‐linear behaviour of wind turbines demands control strategies that guarantee the robustness of the closed‐loop system. Linear parameter‐varying (LPV) controllers adapt their dynamics to the system operating points, and the robustness of the closed loop is guaranteed in the controller design process. An LPV collective pitch controller has been developed within this work to regulate the generator speed in the above rated power production control zone. The performance of this LPV controller has been compared with two baseline control strategies previously designed, on the basis of classical gain scheduling methods and linear time‐invariant robust H∞ controllers. The synthesis of the LPV controller is based on the solution of a linear matrix inequalities system, proposed in a mixed‐sensitivity control scenario where not only weight functions are used but also an LPV model of the wind turbine is necessary. As a contribution, the LPV model used is derived from a family of linear models extracted from the linearization process of the wind turbine non‐linear model. The offshore wind turbine of 5 MW defined in the Upwind European project is the used reference non‐linear model, and it has been modelled using the GH Bladed 4.0 software package. The designed LPV controller has been validated in GH Bladed, and an exhaustive analysis has been carried out to calculate fatigue load reductions on wind turbine components, as well as to analyse the load mitigation in some extreme cases. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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P. M. O. Gebraad F. W. Teeuwisse J. W. van Wingerden P. A. Fleming S. D. Ruben J. R. Marden L. Y. Pao 《风能》2016,19(1):95-114
This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects called the FLOw Redirection and Induction in Steady‐state (FLORIS) model. The FLORIS model predicts the steady‐state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high‐fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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When the installed capacity of wind power becomes high, the power generated by wind farms can no longer simply be that dictated by the wind speed. With sufficiently high penetration, it will be necessary for wind farms to provide assistance with supply‐demand matching. The work presented here introduces a wind farm controller that regulates the power generated by the wind farm to match the grid requirements by causing the power generated by each turbine to be adjusted. Further, benefits include fast response to reach the wind farm power demanded, flexibility, little fluctuation in the wind farm power output and provision of synthetic inertia. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献