State‐space representation of the wind flow model in wind farms

Soleimanzadeh, Maryam; Wisniewski, Rafael; Brand, A.J.

doi:10.1002/we.1594

Cited by 33 publications

(26 citation statements)

References 23 publications

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“…However, if the frequency contents of the tower thrust are assumed fixed, then the fatigue will be monotonic in the STD of the thrust. This is exactly what is shown in Biegel 69 (p. [32][33][34], in which the tower fatigue is plotted versus tower thrust variance, which shows a monotonic trend. The plotted data come from FAST simulations, in which the turbulence intensity is increased from 0.04 to 0.4, and everything else is fixed.…”

Section: The Importance Of the Objective Functionsupporting

confidence: 83%

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Survey of wind farm control—power and fatigue optimization

2014

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The main goal of this paper is to establish the present state of the art for wind farm control. The control area that will be focused on is the mechanical/aerodynamic part, which includes the wind turbines, their power production, fatigue and wakes affecting neighbouring wind turbines. The sub‐objectives in this area of research are as follows: (i) maximizing the total wind farm power production; (ii) following a reference for the total wind farm active power; and (iii) doing this in a manner that minimizes fatigue loading for the wind turbines in the farm. Each of these sub‐objectives is discussed, including the following important control issues: choice of input and output, control method and modelling used for controller design and simulation. The available literature from industry is also considered. Finally, a conclusion is presented discussing the established results, open challenges and necessary research. Copyright © 2014 John Wiley & Sons, Ltd.

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Section: The Importance Of the Objective Functionsupporting

confidence: 83%

“…In Soleimanzadeh et al . , a positive correlation between measured yaw misalignment and WSs in the wake of five Nordex80 turbines is shown on the basis of full scale experimental data. This suggests that the wake really can be directed away from the row by yawing when the wind direction is along the row.…”

Section: Maximize Wind Farm Energymentioning

confidence: 99%

Survey of wind farm control—power and fatigue optimization

2014

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“…Static yaw control, in which upstream turbines intentionally misalign their rotors with incoming winds, has been proven as a promising approach to increasing power extraction, in numerical studies [25,26], but also in wind-tunnel tests [27,28] and full-scale field measurements [29,30]. Studies on dynamic yaw control however are much more scarce.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

2018

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Abstract:In wind farms, wakes originating from upstream turbines cause reduced energy extraction and increased loading variability in downstream rows. The prospect of mitigating these detrimental effects through coordinated controllers at the wind-farm level has fueled a multitude of research efforts in wind-farm control. The main strategies in wind-farm control are to influence the velocity deficits in the wake by deviating from locally optimal axial induction setpoints on the one hand, and steering wakes away from downstream rows through yaw misalignment on the other hand. The current work investigates dynamic induction and yaw control of individual turbines for wind-farm power maximization in large-eddy simulations. To this end, receding-horizon optimal control techniques combined with continuous adjoint gradient evaluations are used. We study a 4 × 4 aligned wind farm, and find that for this farm layout yaw control is more effective than induction control, both for uniform and turbulent inflow conditions. Analysis of optimal yaw controls leads to the definition of two simplified yaw control strategies, in which wake meandering and wake redirection are exploited respectively. Furthermore it is found that dynamic yawing provides significant benefits over static yaw control in turbulent flow environments, whereas this is not the case for uniform inflow. Finally, the potential of combining overinductive axial induction control with yaw control is shown, with power gains that approximate the sum of those achieved by each control strategy separately.

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“…The derivation of a suitable model is thus a central contribution of this paper and we note that other authors, e.g. 18 have developed other simplified wind models. Importantly, the resulting model is dynamic, in the sense that it describes how the wind field evolves over time.…”

Section: Introductionmentioning

confidence: 99%

Real-time wind field reconstruction from LiDAR measurements using a dynamic wind model and state estimation

Towers

Jones

2014

Wind Energ.

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The use of light detection and ranging (LiDAR) instruments offer many potential benefits to the wind energy industry. Although much effort has been invested in developing such instruments, the fact remains that they provide limited spatio-temporal velocity measurements of the wind field. Moreover, LiDAR measurements only provide the radial (line-of-sight) velocity component of the wind, making it difficult to precisely determine wind magnitude and direction, owing to the so-called 'cyclops' dilemma. Motivated by a desire to extract more information from typical LiDAR data, this paper aims to show that it is possible to accurately estimate, in a real-time fashion, the radial and tangential velocity components of the wind field. We show how such reconstructions can be generated through the synthesis of an unscented Kalman filter that employs a low-order dynamic model of the wind to estimate the unmeasured velocities within the wind field, using repeated measurement updates from typical nacelle-mounted LiDAR instruments. This approach is validated upon synthetic data generated from large eddy simulations of the atmospheric boundary layer. The accuracy of the wind field estimates are validated across a variety of beam configurations, look directions, atmospheric stabilities and imperfect measurement conditions. The main outcome of this paper is a technique that offers the potential to accurately reconstruct wind fields from LiDAR data, overcoming the cyclops dilemma in the process. The ultimate aim of this research is to provide reliable gust detection warning systems to offshore construction workers, in addition to accurate wind field estimates for use in preview turbine pitch control systems.

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State‐space representation of the wind flow model in wind farms

Cited by 33 publications

References 23 publications

Survey of wind farm control—power and fatigue optimization

Survey of wind farm control—power and fatigue optimization

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

Real-time wind field reconstruction from LiDAR measurements using a dynamic wind model and state estimation

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