On the implementation and effectiveness of morphological close-open and open-close filters for topology optimization

The design of physical (plant) and control aspects of a dynamic system have traditionally been treated as two separate problems, often solved in sequence. Optimizing plant and control design disciplines separately results in sub-optimal system designs that do not capitalize on the synergistic coupling between these disciplines. This coupling is inherent in most actively controlled dynamic systems, including wind turbines. In this case structural and control design both affect energy production and loads on the turbine. This article presents an integrated approach to achieve system-optimal wind turbine designs using co-design, a design methodology that accounts directly for the synergistic coupling between physical and control system design. A case study, based on multidisciplinary simulation, is presented here that demonstrates a promising increase (up to 8%) in annualized wind turbine energy production compared to the results of a conventional sequential design strategy. The case study also revealed specific synergistic mechanisms that enable performance improvements, which are accessible via co-design but not sequential design.     

Control of variable speed wind turbines: Dynamic models

Owing to concern over the environment, there is much interest in renewable sources of electrical power generation, of which one of the most promising is wind power. Wind turbines exploit this energy source to directly generate electrical power. There are essentially two types of windturbines, namely constant speed and variable speed machines. The purpose of this paper is to investigate the dynamics of variable speed wind turbines and determine suitable models to support the control design task. A basic but widely used dynamic representation of variable speed wind turbines and the corresponding models of the control plant dynamics are initially discussed. More detailed, yet still simple models, are derived separately for the rotor aerodynamics, the drive-train dynamics and the power generation unit dynamics before being combined to form the complete model of the wind turbine dynamics. The resulting combined model, in addition to supporting the control design task, enables the extent, to which the basic models adequate represent the wind turbine, to be assessed. It is concluded that the basic models of variable speed wind turbines are not adequate and do not exhibit all the relevant aspects of the dynamics necessary to support the control design.     

基于FIR神经网络的风电场虚拟风速传感器

风电机组风速传感器易发故障,故障可能导致机组安全风险和发电量损失。针对现行的故障处理方法因与机组控制策略紧密耦合而日益面临挑战,提出了一种基于数据处理的虚拟风速传感器原理与方法：由风电场上风向测量风速计算下风向推算风速,用推算风速取代故障传感器。着重讨论了基于FIR神经网络的推算风速计算方法和计算模型,探讨了系统实现的关键技术。实验证明了虚拟传感器的误差在机组控制系统可接受的程度内。提出的方法独立于机组自身属性,具有普遍适用性,可部署在任意类型的场,在物理传感器故障时向机组提供风速信号,支撑风电机组持续安全运行。     

低风速风力机最大风能追踪的互补滑模控制

针对风力机系统在最大功率点跟踪(MPPT)阶段易受风速等不确定因素的影响,为了进一步提高风力机的风能捕获效率,本文在滑模控制的基础上提出了一种互补滑模控制方法.首先,建立了含有干扰项的风力机系统的线性化模型,采用广义滑模面与互补滑模面相结合的方法设计了互补滑模控制器,并在理论上证明了此控制方法能够有效保证风力机转速跟踪误差的收敛性,且能提高转速跟踪精度.其次,采用风力机专业仿真软件FAST对美国可再生能源实验室(NREL)的600 kW风力机进行了仿真实验,结果表明本文所提出的控制方法不但能提高风力机的风能捕获效率,而且能有效减小转速跟踪误差.最后,将本文所提方法与现有常见的几种控制方法相比较发现:风力机系统在互补滑模控制策略下,具有更高的风能捕获效率和更小的转速跟踪误差.     

Multi-model predictive control for wind turbine operation under meandering wake of upstream turbines

In wind farm operation, the performance and loads of downstream turbines are heavily influenced by the wake of the upstream turbines. Furthermore, the actual wake is more challenging due to the dynamic phenomenon of wake meandering, i.e. the turbine wake often demonstrates dynamic shift over time. To deal with the time-varying characteristics of wake meandering, a multiple model predictive control (MMPC) scheme is applied to the individual pitch control (IPC) based load reduction. The coherence function in the spectral method is used to generate the stochastic wind profile including wake meandering at upstream turbine, and a simplified wake meandering model is developed to emulate the trajectory of the wake center at downstream turbine. The Larsen wake model and Gaussian distribution of wake deficit are applied for composing wind profiles across the rotor of downstream turbines. A set of MMPC controllers are designed based on different linearized state-space models, and are applied in a smooth switching manner. Simulation results show significant reduction in the variation of both rotor speed and blade-root flapwise bending moment using the MMPC based IPC by including the wake meandering, as compared to a benchmark PI controller designed by NREL.     

Adaptive backstepping control of variable speed wind turbines

Variable speed wind turbines maximize the energy capture by operating the turbine at the peak of the power coefficient, however parametric uncertainties in mechanical and electrical dynamics of the system may limit the efficiency of the turbine. In this study, we present an adaptive backstepping approach for the variable speed control of wind turbines. Specifically, to overcome the undesirable effects of parametric uncertainties, a desired compensation adaptation law (DCAL) based controller has been proposed. The proposed method achieves global asymptotic rotor speed tracking, despite the parametric uncertainty on both mechanical and electrical subsystems. Extensive simulation studies are presented to illustrate the feasibility and efficiency of the method proposed.     

Robust nonlinear control strategy to maximize energy capture in a variable speed wind turbine with an internal induction generator

This paper proposes a control strategy to maximize the wind energy captured in a variable speed wind turbine,with an internal induction generator,at low to medium wind speeds.The proposed strategy cont...     

Adaptive and Predictive Control Strategies for Wind Turbine Systems: A Survey

The wind turbine (WT) is a renewable energy conversion device for transformation of kinetic energy from the wind to mechanical energy for subsequent use in different forms. This paper focuses on wind turbine control design strategies. The content is divided into the following parts: 1) An overview of the recent advances that have been made in the application of adaptive and model predictive control strategies for wind turbines. 2) Summarizes some important aspects of modeling of wind turbines for control studies. 3) Provides an outlook on the application of adaptive model predictive control for uncertain systems to stimulate new research interests for wind turbine systems. We provide an overall picture of the research results with evaluation of the merits/demerits.      

A coupled Navier-Stokes/Vortex-Panel solver for the numerical analysis of wind turbines

The present paper introduces a coupled Navier-Stokes/Vortex-Panel solver for the computational study of incompressible high Reynolds number flow around horizontal axis wind turbines. The Navier-Stokes solver is confined to the near-field around one wind turbine blade; the Vortex-Panel method accounts for the far-field of a two-bladed rotor. A robust coupling between both methods is achieved through the spanwise distribution of bound circulation determined by Stokes’ theorem. The coupled solver reduces both artificial dissipation and computational cost compared to a full-domain Navier-Stokes analysis. Results obtained for inviscid and attached viscous flow around an optimal wind turbine blade are compared to a vortex model based on strip theory. Good agreement is found between both models that serves as a validation of the coupled solver for future applications to wind turbines.     

An observer-based blade-pitch controller of wind turbines in high wind speeds

The paper focuses on variable-rotor-speed/variable-blade-pitch wind turbines operating in the region of high wind speeds, where blade pitch and generator torque controllers are aimed at limiting the turbine's energy capture to the rated power value. Coupled design is described of an observer-based blade-pitch control input and a generator torque controller, both of which not requiring the availability of wind speed measurements. Closed loop convergence of the overall control system is proved. The proposed control solution has been validated on a 5-MW three-blade wind turbine using the National Renewable Energy Laboratory (NREL) wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code.     

Selection of Wind Turbine Systems for the Sultanate of Oman

The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades, and the government has struggled to find a solution. In addition, Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040, including solar and wind turbines. Furthermore, the use of small-scale energy from wind devices has been on the rise in recent years. This upward trend is attributed to advancements in wind turbine technology, which have lowered the cost of energy from wind. To calculate the internal and external factors that affect the small-scale energy of wind technologies, the study used a fuzzy analytical hierarchy process technique for order of preference by similarity to an ideal solution. As a result, in the decision model, four criteria, seventeen sub-criteria, and three resources of renewable energy were calculated as options from the viewpoint of the Sultanate of Oman. This research is based on an examination of statistics on energy produced by wind turbines at various locations in the Sultanate of Oman. Further, six distinct miniature wind turbines were investigated for four different locations. The outcomes of this study indicate that the tiny wind turbine has a lot of potential in the Sultanate of Oman for applications such as homes, schools, college campuses, irrigation, greenhouses, communities, and small businesses. The government should also use renewable energy resources to help with the renewable energy issue and make sure that the country has enough renewable energy for its long-term growth.     

Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.     

基于参考输入优化的变速风电机组最大化风能捕获方法

变速风电机组在额定风速以下应用最大功率点跟踪实现最大化风能捕获. 然而, 大惯量风电机组在面对快 速波动的湍流风速时, 因转速调节慢而难以保持运行于最大功率点. 本文研究进一步发现, 平均转速跟踪误差与整 体的风能捕获效率并非单调关系, 这使得当前以减小转速跟踪误差为目标的控制器设计难以有效提升风电机组的 发电效率. 为此, 本文以提升风能捕获效率(而非减小转速跟踪误差)为目标, 提出一种基于参考输入优化的风电机 组最大化风能捕获方法. 考虑到参考转速对风能捕获效率的复杂影响难以准确建模, 本文借助深度确定性策略梯度 (DDPG)强化学习算法实现参考输入优化. 仿真结果表明该方法能够有效提升湍流风下变速风电机组的风能捕获效 率.     

Asymptotic Tracking Control for Wind Turbines in Variable Speed Mode

This paper presents a variable speed control strategy for wind turbines in order to capture maximum wind power. Wind turbines are modeled as a two-mass drive-train system with generator torque control. Based on the obtained wind turbine model, variable speed control schemes are developed. Nonlinear tracking controllers are designed to achieve asymptotic tracking for a prescribed rotor speed reference signal so as to yield maximum wind power capture. Due to the difficulty of torsional angle measurement, an observer-based control scheme that uses only rotor speed information is further developed for global asymptotic output tracking. The effectiveness of the proposed control methods is illustrated by simulation results.      

Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms

Wind energy has become the world’s fastest growing energy source. Although wind farm layout is a well known problem, its solution used to be heuristic, mainly based on the designer experience. A key in search trend is to increase power production capacity over time. Furthermore the production of wind energy often involves uncertainties due to the stochastic nature of wind speeds. The addressed problem contains a novel aspect with respect of other wind turbine selection problems in the context of wind farm design. The problem requires selecting two different wind turbine models (from a list of 26 items available) to minimize the standard deviation of the energy produced throughout the day while maximizing the total energy produced by the wind farm. The novelty of this new approach is based on the fact that wind farms are usually built using a single model of wind turbine. This paper describes the usage of multi-objective evolutionary algorithms (MOEAs) in the context of power energy production, selecting a combination of two different models of wind turbine along with wind speeds distributed over different time spans of the day. Several MOEAs variants belonging to the most renowned and widely used algorithms such as SPEA2 NSGAII, PESA and msPEA have been investigated, tested and compared based on the data gathered from Cancun (Mexico) throughout the year of 2008. We have demonstrated the powerful of MOEAs applied to wind turbine selection problem (WTS) and estimate the mean power and the associated standard deviation considering the wind speed and the dynamics of the power curve of the turbines. Among them, the performance of PESA algorithm looks a little bit superior than the other three algorithms. In conclusion, the use of MOEAs is technically feasible and opens new perspectives for assisting utility companies in developing wind farms.     

直驱式永磁风力发电机软并网与功率调节的控制集成

为实现直驱式永磁同步风力发电机无冲击并网与风能最大跟踪控制, 设计了一种软并网与功率调节一体化的控制集成装置. 基于广义功角特性, 提出了一种对逆变器输出功率进行直接控制, 从而实现最大风能跟踪的控制策略. 新的控制策略可使发电机的转速按所期待的动态运动, 因而具有良好的静态与动态性能. 另外, 该控制律中对电机参数具有很强的鲁棒性, 因而该控制器能适应各种不同参数的同步风力发电机, 成为同步风力发电并网与功率调节的独立装置.     

小型H 型垂直轴风车叶片的设计分析

风力发电机（简称风车）,是一种将风能转化为机械能,电能或热能的转 换装置。比较了垂直轴风力发电机与水平轴风力发电机的优势后,对小型H 型垂直轴风车 叶片的进行了分析,给出了在不同工作环境中的载荷分析,并对叶片的应力计算及校核方法 作了讨论,为小型H 型垂直轴风车的叶片设计提供了参考。     

新型双馈风力发电机有功功率平滑控制策略研究

针对由于风能的不确定性、风力发电机的大惯性以及风力发电系统的响应延迟性等造成的风力发电机输出有功功率在一定范围内有波动的问题,提出了一种新型双馈风力发电机有功功率平滑控制策略。该控制策略在全风速范围内采用变浆与变速协调控制策略,并在其基础上增加了一个有功功率误差控制环节,将转子电压辅助控制指令值作为反馈量加入原来的转子电压控制指令值,通过控制SPWM脉冲发生器来实现风力发电机定子输出有功功率的平滑控制。Matlab/Simulink仿真结果表明,与传统有功功率控制策略相比,该新型有功功率平滑控制策略有效抑制了双馈风力发电机输出有功功率的波动。     

Feedforward Control for Wind Turbine Load Reduction with Pseudo-LIDAR Measurement

A gain-scheduled feedforward controller, based on pseudo-LIDAR (light detection and ranging) wind speed measurement, is designed to augment the baseline feedback controller for wind turbine’s load reduction in above rated operation. The pseudo-LIDAR measurement data are generated from a commercial software – Bladed using a designed sampling strategy. The nonlinear wind turbine model has been simplified and linearised at a set of equilibrium operating points. The feedforward controller is firstly developed based on a linearised model at an above rated wind speed, and then expanded to the full above rated operational envelope by employing gain scheduling strategy. The combined feedforward and baseline feedback control is simulated on a 5 MW industrial wind turbine model. Simulation studies demonstrate that the proposed control strategy can improve the rotor and tower load reduction performance for large wind turbines.     

Adaptive Continuous Neural Pitch Angle Control for Variable‐Speed Wind Turbines

As wind energy becomes one of the fastest growing renewable energy resources, the control of large‐scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. In this paper, an adaptive neural pitch angle control strategy is proposed for the variable‐speed wind turbines (VSWT) operating in pitch control region. The control objective is to maintain the rotor speed and generator power at the prescribed reference values in the presence of external disturbance, without the need of the information of system parameters and aerodynamics. First, the order of the system dynamics is increased by defining a filtered regulation error. By this means, the non‐affine characteristics of the VSWT model is transformed into a simple affine control problem and thus the feedback linearization technique can be employed. The continuousness of control signal is also guaranteed to relax the requirement on the bandwidth of actuators, and the mechanical load on pitching systems is reduced. Subsequently, an online learning approximator (OLA) is utilized to estimate the unknown nonlinear aerodynamics of the wind turbine and extend the practicability of the proposed adaptive parameter‐free controller. In addition, a high‐gain observer is implemented to obtain an estimation of rotor acceleration, which rejects the need of additional sensors. Rigid theoretical analysis guarantees the tracking of rotor speed/generator power and the boundedness of all other signals of the closed‐loop system. Finally, the effectiveness of the proposed scheme is testified via the Wind Turbine Blockset simulation package in Matlab/Simulink environment. Moreover, comparison results reveal that the introduced solution is able to provide better regulation performance than the conventional PI counterpart.