06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7

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Publication Type: search.filters.UBSTyp.KonferenzbeitragAuthor: search.filters.author.Schlipf, David

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Now showing 1 - 10 of 23
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    Comparison of feedforward and model predictive control of wind turbines using LIDAR
    (2012) Schlipf, David; Pao, Lucy Y.; Cheng, Po Wen
    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 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.
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    Optimization of floating offshore wind turbine platforms with a self-tuning controller
    (2017) Lemmer, Frank; Müller, Kolja; Yu, Wei; Schlipf, David; Cheng, Po Wen
    The dynamic response of floating offshore wind turbines is complex and requires numerous design iterations in order to converge at a cost-efficient hull shape with reduced responses to wind and waves. In this article, a framework is presented, which allows the optimization of design parameters with respect to user-defined criteria such as load reduction and material costs. The optimization uses a simplified nonlinear model of the floating wind turbine and a self-tuning model-based controller. The results are shown for a concrete three-column semi-submersible and a 10MW wind turbine, for which a reduction of the fluctuating wind and wave loads is possible through the optimization. However, this happens at increased material costs for the platform due to voluminous heave plates or increased column spacing.
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    Nonlinear model predictive control of floating wind turbines
    (2013) Schlipf, David; Sandner, Frank; Raach, Steffen; Matha, Denis; Cheng, Po Wen
    In this work a nonlinear model predictive control method for a floating wind turbine is presented. A reduced nonlinear model including disturbance preview of wind and waves is derived and implemented to compute optimal input trajectories for collective pitch and the generator torque. A cost functional is introduced which fulfills all desired constraints and controller goals for above rated wind conditions. The controller is tested for extreme and fatigue load cases and a significant reduction of the power and rotor speed deviations is obtained. Furthermore, ultimate tower loads and damage equivalent loads on shaft and blades are decreased. Although more detailed testing is necessary, this preliminary results show the advantages of nonlinear model predictive control for floating wind turbines.
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    Nonlinear model predictive control of floating wind turbines with individual pitch control
    (2014) Raach, Steffen; Schlipf, David; Sandner, Frank; Matha, Denis; Cheng, Po Wen
    In this work a nonlinear model predictive controller with individual pitch control for a floating offshore wind turbine is presented. An aerodynamic model of the collective pitch control approach is extended by describing pitching and yawing moments based on rotor disk theory. This extension is implemented in a reduced nonlinear model of the floating wind turbine including disturbance preview of wind speed, linear vertical and horizontal wind shear, and wave height to compute optimal input trajectories for the individual pitch control inputs and the generator torque. An extended cost functional for individual pitch control is proposed based on the collective pitch control approach. The controller is evaluated in aero-servo-hydro-elastic simulations of a 5MW reference wind turbine disturbed by a three-dimensional stochastic turbulent wind field. Results show a significant blade fatigue load reduction compared to a baseline controller through minimizing yawing and pitching moments on the rotor hub while maintaining the advantages of the model predictive control approach with collective pitch control.
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    Flatness-based feedforward control of wind turbines using Lidar
    (2014) Schlipf, David; Cheng, Po Wen
    Current lidar technology is offering a promising opportunity to take a fresh look at wind turbine control. This work evaluates a flatness-based feedforward approach, that allows to calculate the control action based on trajectories of the rotor speed and tower motion using wind measurements. The trajectories are planned online considering actuator constrains to regulate the rotor speed and minimize tower movements. The feedforward signals of the collective pitch and generator torque update can be combined with conventional feedback controllers. This facilitates the application on commercial wind turbines. Simulations using a realistic lidar simulator and a full aero-elastic model show considerable reduction of tower and shaft loads.
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    Realistic simulations of extreme load cases with lidar-based feedforward control
    (2017) Hagemann, Tim; Haizmann, Florian; Schlipf, David; Cheng, Po Wen
    This work presents the development of a simulation environment which allows to simulate realistic extreme events with lidar-based feedforward control. This environment includes turbulent wind fields including extreme events, wind evolution and wind field scanning with a nacelle-based lidar system. It is designed to simulate lidar-based controllers in a realistic environment. In addition, a controller extension is proposed to identify and mitigate extreme events in wind fields based on lidar measurements. The combination of this extreme event controller with the realistic simulation environment is a promising tool for load reductions in wind turbines.
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    Load analysis of look-ahead collective pitch control using LIDAR
    (2010) Schlipf, David; Fischer, Tim; Carcangiu, Carlo Enrico; Rossetti, Michele; Bossanyi, Ervin
    In 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.
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    Statistical load estimation using a nacelle-based lidar system
    (2010) Bischoff, Oliver; Hofsäß, Martin; Rettenmeier, Andreas; Schlipf, David; Siegmeier, Björn
    The paper presents the results of statistical load analyses based on data measured at the 5MW AREVA Wind M5000 onshore prototype. Measurements with standard meteorological measurement devices are analysed and compared to measurements with a pulsed LIDAR system which is enhanced with a multi-purpose scanning device installed on the top of the nacelle of the turbine. Based on these measurements statistical summaries of relevant meteorological parameters have been used for normative procedures to calculate the mechanical loads which occur at the wind energy turbine. It could be verified that LIDAR systems can substitute standard measurement devices for a load estimation of wind energy turbines.
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    Development of a wind turbine LiDAR simulator
    (2009) Schlipf, David; Trujillo, Juan José; Basterra, Valeria; Kühn, Martin
    Remote sensing techniques like LiDAR offer many novel applications to the wind energy community, e.g. fast and accurate measurements of inflow and wake wind fields from the turbine nacelle. The prospects of such a new technique are evaluated with a software tool simulating a nacelle-based LiDAR system. The paper presents the implementation and application of a simulator that has been conceived to support the design of wind field scanning procedures. The tool helps to optimize the hardware setup, scanning trajectories and frequency. Furthermore it can be coupled with an aeroelastic code with the aim of developing a predictive control based on remote sensing.
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    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 Wen
    This 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.