06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Comparison of feedforward and model predictive control of wind turbines using LIDAR(2012) Schlipf, David; Pao, Lucy Y.; Cheng, Po WenLIDAR 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 such as feedforward control and model predictive control. This paper compares a nonlinear model predictive controller and a feedforward controller to a baseline controller. Realistic wind "measurements" are obtained using a detailed simulation of a LIDAR system. A full lifetime comparison shows the advantages of using the wind predictions to reduce wind turbine fatigue loads on the tower and blades as well as to limit the blade pitch rates. The results illustrate that the feedforward controller can be combined with a tower feedback controller to yield similar load reductions as the model predictive controller.Item Open Access Tidal current turbine wake and park layout in transient environments(2014) Arnold, Matthias; Cheng, Po Wen; Daus, Philipp; Biskup, FrankDue to orbital velocities of the waves, the characteristics of tidal current turbines change over time. Therefore the induction factor and subsequent the wake is time dependent. Within the present research this time dependency is investigated by using Computational Fluid Dynamics (CFD) with Virtual Free Surface (VFS) and Actuator Disc (ACD) models. Based on this setup several different wave and current scenarios are simulated and analyzed with respect to the transient velocities in the turbine wake. Special respect is taken to the velocity undulations radiated by the changing apparent velocities in the rotor plane. These undulations move with the wake of the tidal current turbines and increase wave loads on 2nd row turbines in a park. This paper presents an efficient method for simulation of wave and park interactions and investigates dynamic turbine wakes under a large variety of parameters. Based on these simulations a suggestion for a tidal park design with respect to a balance of fatigue loads and power output is concluded.Item Open Access Load analysis of look-ahead collective pitch control using LIDAR(2010) Schlipf, David; Fischer, Tim; Carcangiu, Carlo Enrico; Rossetti, Michele; Bossanyi, ErvinIn a detailed analysis the benefit of LIDAR assisted collective pitch control is evaluated, by using a realistic LIDAR simulator and comparing it to an advanced feedback controller. With the proposed look-ahead controller best load reduction can be observed for high turbulence and high wind speed. Damage equivalent loads on tower and blades are reduced up to 20% and 10%, respectively.Item Open Access Optimization of a feed-forward controller using a CW-lidar system on the CART3(2015) Haizmann, Florian; Schlipf, David; Raach, Steffen; Scholbrock, Andrew; Wright, Alan; Slinger, Chris; Medley, John; Harris, Michael; Bossanyi, Ervin; Cheng, Po WenThis work presents results from a new field-testing campaign conducted on the three-bladed Controls Advanced Research Turbine (CART3) at the National Renewable Energy Laboratory in 2014. Tests were conducted using a commercially available, nacelle-mounted continuous-wave lidar system from ZephIR Lidar for the implementation of a lidar-based collective pitch feed-forward controller. During the campaign, the data processing of the lidar system was optimized for higher availability. Furthermore, the optimal scan distance was investigated for the CART3 by means of a spectra-based analytical model and found to match the lidar's capabilities well. Throughout the campaign the predicted correlation between the lidar measurements and the turbine's reaction was confirmed from the measured data. Additionally, the baseline feedback controller's gains were tuned based on a simulation study that included the lidar system to achieve further load reductions. This led to some promising first results, which are presented at the end of this paper.Item Open Access Testing of frozen turbulence hypothesis for wind turbine applications with a scanning LIDAR system(2011) Schlipf, David; Trabucchi, Davide; Bischoff, Oliver; Hofsäß, Martin; Mann, Jakob; Mikkelsen, Torben; Rettenmeier, Andreas; Trujillo, Juan José; Kühn, MartinTaylor’s frozen turbulence hypothesis is tested in its applicability for wind turbine applications. In this research full field measurements are performed at a test site for multi-megawatt wind turbines by means of a pulsed LIDAR with a scanning device. The system is installed at the top of the nacelle of a 5MW wind turbine. It provides simultaneous wind speed, with a maximum sampling rate of 5 Hz, at different stations parallel to the mean wind. Measurements in a range between 0.4 and 1.6 rotor diameter are performed following several two and three dimensional trajectories. The spectral characteristics of measurements taken simultaneously at different separation distances are studied. The scanning strategy which maximizes the wavenumber region where results are consistent with Taylor’s hypothesis is assessed. The best results are achieved by a horizontal sliding trajectory with valid wavenumbers up to 0.125 rad/m.Item Open Access Collective pitch feedforward control of floating wind turbines using lidar(2015) Schlipf, David; Simley, Eric; Lemmer, Frank; Pao, Lucy; Cheng, Po WenIn this work a collective pitch feedforward controller for floating wind turbines is presented. The feedforward controller provides a pitch rate update to a conventional feedback controller based on a wind speed preview. The controller is designed similar to the one for onshore turbines, which has proven its capability to improve wind turbine control performance in field tests. In a first design step, perfect wind preview and a calm sea is assumed. Under these assumptions the feedforward controller is able to compensate almost perfectly the effect of changing wind speed to the rotor speed of a full nonlinear model over the entire full load region. In a second step, a nacelle-based lidar is simulated scanning the same wind field which is used also for the aero-hydro-servo-elastic simulation. With model-based wind field reconstruction methods, the rotor effective wind speed is estimated from the raw lidar data and is used in the feedforward controller after filtering out the uncorrelated frequencies. Simulation results show that even with a more realistic wind preview, the feedforward controller is able to significantly reduce rotor speed and power variations. Furthermore, structural loads on the tower, rotor shaft, and blades are decreased. A comparison to a theoretical investigation shows that the reduction in rotor speed regulation is close to the optimum.Item Open Access Lidar technology for the German offshore test site "alpha ventus" - joint project in measurement development(2008) Rettenmeier, Andreas; Schlipf, David; Wächter, Matthias; Käsler, Yvonne; Mellinghoff, Harald; Siegmeier, Björn; Reeder, Lennard; Kühn, MartinThis paper describes the content of the joint research project "Development of LiDAR measurement techniques for the German offshore test site" and its first results. The objective is to develop reliable and standardised remote sensing techniques for various new applications in the wind energy community and to support other RAVE1 projects at the German offshore test site "alpha ventus". The first measurement campaign dealt with the comparison of wind parameters measured by common anemometry in a height of up to 103 m and LiDAR data measured up to 220 m height. The first results show very good agreement when the two techniques are compared as to wind speed, wind direction and power curve determination at a 5 MW wind turbine. The status of the development of a wind field scanner for nacelle-based LiDAR measurements is described and an outlook to the forthcoming work is given.Item Open Access Direct speed control using LIDAR and turbine data(2013) Schlipf, David; Fleming, Paul; Kapp, Stefan; Scholbrock, Andrew; Haizmann, Florian; Belen, Fred; Wright, Alan; Cheng, Po WenLIDAR systems are able to provide preview information of the wind speed in front of wind turbines. One proposed use of this information is to increase the energy capture of the turbine by adjusting the rotor speed directly to maintain operation at the optimal tip-speed ratio, a technique referred to as Direct Speed Control (DSC). Previous work has indicated that for large turbines the marginal benefit of the direct speed controller in terms of increased power does not compensate for the increase of the shaft loads. However, the technique has not yet been adequately tested to make this determination conclusively. Further, it is possible that applying DSC to smaller turbines could be worthwhile because of the higher rotor speed fluctuations and the small rotor inertia. This paper extends the previous work on direct speed controllers. A DSC is developed for a 600 kW experimental turbine and is evaluated theoretically and in simulation. Because the actual turbine has a mounted LIDAR, data collected from the turbine and LIDAR during operation are used to perform a hybrid simulation. This technique allows a realistic simulation to be performed, which provides good agreement with theoretical predictions.Item Open Access Prospects of optimization of energy production by LIDAR assisted control of wind turbines(2011) Schlipf, David; Kapp, Stefan; Anger, Jan; Bischoff, Oliver; Hofsäß, Martin; Rettenmeier, Andreas; Kühn, MartinIn the presented work two approaches to increase the energy production of wind turbines are studied assuming the usage of a wind speed measurement provided by a nacelle based LIDAR system: The first approach uses the knowledge of the incoming wind speed to assist variable speed control. The second approach uses the wind direction information measured by a LIDAR system for yaw control. From this first analysis only marginal benefit can be gained by the LIDAR assisted speed control, but an increase of energy production by a couple of percent can be expected by LIDAR assisted yaw control.