Dynamic modelling and design of various robust sliding mode controls for the wind turbine with estimation of wind speed

The main propose of this paper is extracting the maximum efficiency from variable speed wind turbine, which is modelled as an electromechanical system with two masses dynamics. The maximum efficiency can be obtained by tracking the optimal rotor speed, which is controlled by the generator torque as the input. One of the most important information that is required for designing of the control system is the measurement of the effective wind velocity. In this paper, a new ANFIS-based method for estimating the effective wind velocity is developed. The aerodynamic torque has a direct relationship with the power coefficient. So in this paper, power coefficient of WindPACT 1.5 MW turbine as a function of tip speed ratio (TSR) and blade pitch angle is considered. Then, three control methods based on high order sliding mode controllers are examined. The rotor speed and the wind velocity are the only variables required in the design of second and third order sliding mode controllers. FAST (Fatigue, Aerodynamics, Structures and Turbulence) is valid software that offers a fairly complete model of the wind turbine. Results of this paper are validated using FAST. Performance of the designed controllers is compared in terms of the generator torque and desired rotor speed tracking. Finally, the doubly fed induction generator (DFIG) is controlled such that the objectives of reactive power minimization and tracking the desired generator torque are achieved. Two main hindrances in designing the control systems are the uncertainties and the lack of sufficient information on measurements. Therefore robust performance of designed controllers against the model uncertainties is investigated.     

Application of bamboo laminates in large-scale wind turbine blade design?

From the viewpoint of material and structure in the design of bamboo blades of large-scale wind turbine, a series of mechanical property tests of bamboo laminates as the major enhancement materials for blades are presented. The basic mechanical characteristics needed in the design of bamboo blades are brie?y introduced. Based on these data, the aerodynamic-structural integrated design of a 1.5 MW wind turbine bamboo blade relying on a conventional platform of upwind, variable speed, variable pitch, and doubly-fed generator is carried out. The process of the structural layer design of bamboo blades is documented in detail. The structural strength and fatigue life of the designed wind turbine blades are certified. The technical issues raised from the design are discussed. Key problems and direction of the future study are also summarized.     

基于LiToSim平台的海上风机过渡段优化软件开发

针对海上风机过渡段结构,考虑风机多尺度优化模型和所受环境荷载采取极端情况下,引入双向渐进结构拓扑优化方法,以全局应力最小化为目标、体积为约束,对风机过渡段进行优化设计;并在自主研发的LiToSim平台基础上,嵌入风机优化数值计算程序,最终形成一款关于海上风机过渡段拓扑优化的定制化软件TUR/TOPT.借助定制化软件TUR/TOPT平台,对比过渡段传统柔度优化与应力优化结果,突显出应力优化在减材设计过程中结构应力明显降低且能有效避免应力集中等方面的优势;TUR/TOPT软件的生成在风机建设选型过程中具有重要指导价值.     

Multivariable adaptive variable structure disturbance rejection control for DFIG system

A novel variable structure and disturbance rejection control strategy for a wind turbines equipped with a double fed induction generator based on stator‐flux‐oriented vector control is presented. According to estimation of maximum power operation points of wind turbine under stochastic wind velocity profiles and tracking them using traditional offline gain, scheduling and innovative adaptive online method is necessary. To demonstrate the effectiveness of the proposed control strategy, the estimation of maximum operating power point of wind turbine and tracking it under stochastic wind velocity profiles has been considered as a test case. Simulation results show the validity of the proposed technique. © 2014 Wiley Periodicals, Inc. Complexity 21: 50–62, 2016     

Iterative solver approach for turbine interactions: application to wind or marine current turbine farms

This paper presents a numerical investigation for the computation of wind or marine current turbines in a farm. A 3D unsteady Lagrangian vortex method is used together with a panel method in order to take into account for the turbines. In order to enforce the boundary condition onto the panel elements, a linear matrix system is defined. Solving general linear matrix systems is a topic with important scientific literature. But the main concern here is the application to a dedicated matrix which is non-sparse, non-symmetric, neither diagonally dominant nor positive-definite. Several iterative approaches were tested and compared. But after some numerical tests, a Bi-CGSTAB method was finally chosen. The main advantage of the presented method is the use of a specific preconditioner well suited for the desired application. The chosen implementation proved to be very efficient with only 3 iterations of our preconditioned Bi-CGSTAB algorithm whatever the turbine geometrical configuration. Although developed for wind or marine turbines, the proposed algorithm is absolutely not restricted to these cases, and can be applied to many others. At the end of the paper, some applications (specifically, wake computations) in a farm are presented, along with a quantitative assessment of the computational time savings brought by the iterative approach.     

A dynamic wind farm aggregate model for the simulation of power fluctuations due to wind turbulence

An important aspect related to wind energy integration into the electrical power system is the fluctuation of the generated power due to the stochastic variations of the wind speed across the area where wind turbines are installed. Simulation models are useful tools to evaluate the impact of the wind power on the power system stability and on the power quality. Aggregate models reduce the simulation time required by detailed dynamic models of multiturbine systems.In this paper, a new behavioral model representing the aggregate contribution of several variable-speed-pitch-controlled wind turbines is introduced. It is particularly suitable for the simulation of short term power fluctuations due to wind turbulence, where steady-state models are not applicable.The model relies on the output rescaling of a single turbine dynamic model. The single turbine output is divided into its steady state and dynamic components, which are then multiplied by different scaling factors. The smoothing effect due to wind incoherence at different locations inside a wind farm is taken into account by filtering the steady state power curve by means of a Gaussian filter as well as applying a proper damping on the dynamic part.The model has been developed to be one of the building-blocks of a model of a large electrical system, therefore a significant reduction of simulation time has been pursued. Comparison against a full model obtained by repeating a detailed single turbine model, shows that a proper trade-off between accuracy and computational speed has been achieved.     

Elastic blade root connection in wind turbine using flexible elements from composites

The aim of an elastic blade root connection with a hub is to decrease loads in the blade root section during wind gusts. Two designs of connection were considered: for the load reduction on the blade in operating regime and for stopped blade unloading under storm wind. In the first case two versions of joint were discussed: the first one — with hinges and U-shaped composite beams, the second one — formed with straight beams oriented in different directions. Both joints have low torsional stiffness in wind direction and much higher stiffnesses around two other axes. Formulas for angular stiffnesses and the methods of obtaining the nonlinear behavior of the joint are presented. The objective of the flexible spar was to allow the blades to bend back out of the wind to reduce loads when the wind turbine was stationary in storm conditions. Calculations supported the feasibility of such a design. With a low torsional stiffness, spar (which can be rigidly connected to the blade) acts as a pitching beam for turbine control. A compound spar design consisting of pultruded bars clamped through specified distance was proposed. Torsional stiffnesses of different types of spars with equal specified bending rigidity were compared.Published in Mekhanika Kompozitnykh Materialov, Vol. 32, No. 3, pp. 388–400, May–June, 1996.     

Proximity search heuristics for wind farm optimal layout

A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently-proposed proximity search paradigm. Computational results on very large scale instances involving up to 20,000 potential turbine sites prove the practical viability of the overall approach.     

The impact of wind uncertainty on the strategic valuation of distributed electricity storage

The intermittent nature of wind energy generation has introduced a new degree of uncertainty to the tactical planning of energy systems. Short-term energy balancing decisions are no longer (fully) known, and it is this lack of knowledge that causes the need for strategic thinking. But despite this observation, strategic models are rarely set in an uncertain environment. And even if they are, the approach used is often inappropriate, based on some variant of scenario analysis—what-if analysis. In this paper we develop a deterministic strategic model for the valuation of electricity storage (a battery), and ask: “Though leaving out wind speed uncertainty clearly is a simplification, does it really matter for the valuation of storage?”. We answer this question by formulating a stochastic programming model, and compare its valuation to that of its deterministic counterpart. Both models capture the arbitrage value of storage, but only the stochastic model captures the battery value stemming from wind speed uncertainty. Is the difference important? The model is tested on a case from Lancaster University’s campus energy system where a wind turbine is installed. From our analysis, we conclude that considering wind speed uncertainty can increase the estimated value of storage with up to 50 % relative to a deterministic estimate. However, we also observe cases where wind speed uncertainty is insignificant for storage valuation.     

气动、结构、载荷相协调的大型风电叶片自主研发进展

从叶片设计的3个关键环节（气动设计、结构设计和载荷评估）出发,对叶片自主研发进展进行了总结分析．在气动设计方面,概述了计算流体动力学（computational fluid dynamics, CFD）方法、涡方法和叶素动量（blade element momentum, BEM）方法,并依据工程中广泛应用的BEM方法,指出了低风速区风电叶片的解决思路;在结构设计方面,简要概述了基于梁模型的传统设计分析方法,分析了其在大型复合材料叶片薄壳结构上的不足,并对有限元方法（finite element method, FEM）在叶片结构分析中的应用进展进行了介绍;在载荷评估方面,介绍了其对叶片和整机其它部件的影响,阐述了载荷预估方面的工作进展．然后,通过分析3个关键环节之间的相互关系,得到如下结论:建立气动、结构和载荷相协调的叶片优化设计体系,才能真正满足高效低成本的需要．最后,指明了需要进一步研究的主要方向,即高效低载翼型研究,结构非线性有限元分析,气动-结构耦合研究,设计标准制定．最终目标是建立适合中国风资源特点的叶片研发体系,推动我国风电产业发展.     

Influence of turbulence on the performance of a laboratory scale HAWT

The oncoming wind to horizontal axis wind turbines (HAWT) may change its speed and direction stochastically in time. Hence, turbine blades are exposed to flows both with fluctuating angle of attack and fluctuating yaw angles. The modern wind turbines are reacting to those changes by pitch angle and torque control not only to exploit as much power as possible but also stabilize energy production and prevent any damage of the turbine. However, time scales of wind fluctuations and sudden changes of wind properties can be very short and with very high in amplitude. In the present study we focus on the influence of turbulence on the performance of a HAWT. Main motivation of the investigations is to figure out best strategies for the aerodynamic design of the blades operating under turbulent conditions. A laboratory scale HAWT and a performance measurement set-up are employed to measure the influence of the oncoming wind. The tests are conducted in the closed loop wind tunnel of our institute. The test section of the tunnel is 1.87 m in width, 1.4 m in height and 2 m in length. The rotor blades are specially designed and optimized for this wind tunnel and the generator used. The turbulence is generated by two static squared mesh grids; fine and coarse one. Hence, two mainly different turbulence scales are obtained. In addition, the distance between the wind-turbine and the grid is adjusted to have additional sub-turbulence scales for each grid. The turbulence is nearly isotropic and decays in the flow direction. The developments of Taylor's micro scale (λ_g) and integral scale (L_g) of the turbulence in the flow direction at various incoming wind velocities (8−16 m/s) are measured. Hence, the facility allows to expose the wind-turbine to turbulence with various energy and length scale content. Those measurements are conducted with hot-wire anemometry in the absence of the wind-turbine. Upstream and downstream turbulence intensities (TI) distributions are measured to give insight on the surrounding free stream and turbine wake interaction and how can different turbulence eddies scales contribute in the influence of the performance of the turbine. Performance measurements are conducted with and without turbulence and the results are compared. The study shows that the higher the turbulence, the more the power extracted by the turbine. This is due to the higher interaction of large eddies with the turbine wake and with the boundary layer, which helps to keeping it attached. Furthermore, higher TI's help in suppressing the tip vortex, thus, reduce turbine tip losses. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Design of an active fault tolerant control system for a simulated industrial steam turbine

An active fault tolerant control (FTC) scheme is proposed in this paper to accommodate for an industrial steam turbine faults based on integration of a data-driven fault detection and diagnosis (FDD) module and an adaptive generalized predictive control (GPC) approach. The FDD module uses a fusion-based methodology to incorporate a multi-attribute feature via a support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) classifiers. In the GPC formulation, an adaptive configuration of its internal model has been devised to capture the faulty model for the set of internal steam turbine faults. To handle the most challenging faults, however, the GPC control configuration is modified via its weighting factors to demand for satisfactory control recovery with less vigorous control actions. The proposed FTC scheme is hence able to systematically maintain early FDD with efficient fault accommodation against faults jeopardizing the steam turbine availability. Extensive simulation tests are conducted to explore the effectiveness of the proposed FTC performances in response to different categories of steam turbine fault scenarios.     

A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines

The small and fluctuating samples of lubricating oil data render the wear trend prediction a challenging task in operation and maintenance management of wind turbine gearboxes. To deal with this problem, this paper puts forward a method to enhance the prediction accuracy and robustness of the grey prediction model by introducing multi-source information into traditional grey models. Multi-source information is applied by creating a mapping sequence according to the sequence to be predicted. The significance of the key parameters in the proposed model was investigated by numerical experiments. Based on the results from the numerical experiments, the effectiveness of the proposed method was demonstrated using lubricating oil data captured from industrial wind turbine gearboxes. A comparative analysis was also conducted with a number of selected other models to illustrate the superiority of the proposed model in dealing with small and fluctuating data. Prediction results show that the proposed model is able to relax the quasi-smooth requirement of data sequence and is much more robust in comparison to exponential regression, linear regression and non-equidistance GM(1,1) models.     

Modeling,simulation and control a hydraulic servo system

Hydraulic actuators are widely used in industrial applications due to several advantages like large force and torque, high power to weight ratio, rapid and accurate response. In this paper a nonlinear model of a hydraulic servo system is developed by means of the associated differential equations and then simulated using Matlab techniques. The model describes the behavior of a servo system FESTO TP511 with MOOG-DDV633 servovalve and includes the nonlinearities of friction forces, valve dynamics, oil compressibility and load influence. The nonlinear model is used to design an optimal controller based on estimated state parameters through simulation. A digital control platform based on Atmel ATmega8535 microcontroller is used to compare the behavior of hydraulic system under PD and optimal control. The control platform was designed like an interface between PC and process: the control algorithm runs on PC and the digital platform assures amplifying, filtering and data communication functions. Both simulation and experimental results are provided to show the effectiveness of the proposed model and control method. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Stall-delay modelling of wind turbine blades

Most aerodynamic design tools for horizontal-axial wind turbines are based on the blade-element momentum theory (BEM). Due to the nature of this theory, the design tools need 2-D steady sectional lift and drag curves as an input. In practice, flow over a wind turbine rotor blade is neither two-dimensional nor steady, and is affected by rotation. Pioneering experiments have identified a consequence: at inboard rotor blade sections stall is delayed. This so-called Himmelskamp effect [1] gives a larger lift than predicted and, as a result, a higher power and loading than expected. Consequently, an aerodynamic model is needed to explain and predict sectional lift and drag under rotating conditions. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Two Way Coupled Micro/Meso Scale Method for Wind Farms

Wind turbines extract energy from the approaching flow field resulting in reduced wind speeds, increased turbulence and a wake downstream of the wind turbine. The wake has a multitude of negative effects on downstream wind turbines. This includes reduced efficiency and increased unsteadiness resulting in vibrations and potentially in material fatigue. Moreover, the maintenance can increase compared to non-interfering wind turbines. The simulation of these effects is challenging. Computational fluid dynamics (CFD) simulations of these large and complex geometries requires exceedingly large computational resources. With present Reynolds Averaged Navier-Stokes (RANS) or Large Eddy Simulation (LES) based CFD methods it is virtually impossible to perform such simulations of the interaction between individual wind turbines in a complete wind turbine farm. Coupling to the mesoscale accounting for local weather situations becomes yet more challenging. This is due to the wide range of length and time scales that have to be considered for these simulations and therefore the tremendous computational power needed to perform such simulations. To investigate these effects we propose to combine ideas from existing methods, the Coarse-Grid-CFD (CGCFD) ( [1]) developed at the KIT and the meso-/ micro scale method developed at the University of Thessaloniki ( [2]). Goal of the proposed methodology is to provide a numerical method that allows to implement a wind farm in a meso-scale weather simulation which includes two-way coupling. Thus both the micro and the meso scale wind and energy production of wind farms can be addressed. This proposed multi scale coupling strategy can also be applied in two hierarchies reducing the numerical effort of the global approach yet more. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Suppression of chaotic behavior in horizontal platform systems based on an adaptive sliding mode control scheme

This work presents an adaptive sliding mode control scheme to elucidate the robust chaos suppression control of non-autonomous chaotic systems. The proposed control scheme utilizes extended systems to ensure that continuous control input is obtained in order to avoid chattering phenomenon as frequently in conventional sliding mode control systems. A switching surface is adopted to ensure the relative ease in stabilizing the extended error dynamics in the sliding mode. An adaptive sliding mode controller (ASMC) is then derived to guarantee the occurrence of the sliding motion, even when the chaotic horizontal platform system (HPS) is undergoing parametric uncertainties. Based on Lyapunov stability theorem, control laws are derived. In addition to guaranteeing that uncertain horizontal platform chaotic systems can be stabilized to a steady state, the proposed control scheme ensures asymptotically tracking of any desired trajectory. Furthermore, the numerical simulations verify the accuracy of the proposed control scheme, which is applicable to another chaotic system based on the same design scheme.     

海上浮式风力机及其动力学问题

深水风资源更为丰富,随着科技进步风电场正逐步向水深百米及以上的海域发展．海上浮式风力机、浮式基础以及系泊系统作业时,受到风浪流等的联合作用．就不同海上浮式风力机形式及其典型结构对应的气动载荷、水动力载荷,浮式风力机系统与环境动力的耦合问题、处理方法和可能的发展方向作了简要的评述．充分考虑作业背景的环境流场和风力机尺度,针对不同的流动特征综合各种理论方法和计算手段,更为准确地进行空气动力学-水动力学-控制系统-结构耦合分析是研究的难点和发展方向.     

Multivariate sensitivity analysis for dynamic models with both random and random process inputs

Dynamic models with both random and random process inputs are frequently used in engineering. However, sensitivity analysis (SA) for such models is still a challenging problem. This paper, therefore, proposes a new multivariate SA technique to aid the safety design of these models. The new method can decompose the SA of dynamic models into a series of SA of their principle components based on singular value decomposition, which will make the SA of dynamic models much more efficient. It is shown that the effect of both random and random process inputs on the uncertainty of dynamic output can be measured from their effects on both the distributions and directions of the principle components, based on which the individual sensitivities are defined. The generalized sensitivities are then proposed to synthesize the information that is spread between the principal components to assess the influence of each input on the entire uncertainty of dynamic output. The properties of the new sensitivities are derived and an efficient estimation algorithm is proposed based on unscented transformation. Numerical results are discussed with application to a hydrokinetic turbine blade model, where the new method is compared with the existing variance-based method.