06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

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

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Institute: search.filters.UBSInstitut.Institut für FlugzeugbauSubject: search.filters.subject.624

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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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    Development of a model predictive controller for floating offshore wind turbines
    (2020) Nann, Samuel
    In this work, an Economic Model Predictive Controller for a floating offshore wind turbine is presented. The classical Model Predictive Control for floating offshore wind turbines provides promising results. In addition, research on onshore wind turbines revealed the potential of the economic control method, which can improve the closed-loop behavior and simplify the control design in comparison to the classical version of this control method. The aim of this work is, to develop a novel Economic Model Predictive Controller for a floating offshore wind turbine based on these two research results. A simplified low order model of a floating offshore wind turbine serves as a basis for the controller design. Including the disturbance preview and constraints, the controller computes optimal trajectories for the blade pitch and the generator torque. To apply the control technique to a floating offshore wind turbine two things have to be done: Firstly, the cost function is designed, to fulfill the main objectives of, maximizing the generated power and alleviating the structural fatigues. Secondly, the constraints are integrated into the control problem. After selecting a suitable solver, the controller is discretized and scaled, thus a proper implementation and smooth operation is possible. Afterwards, the successful functioning of the algorithm, a multi-objective optimization is done, to find appropriate weights to adjust the cost function for the required objectives. Finally, the developed controller is tested with realistic wind and wave disturbances. A significant reduction of the standard deviation of the generated power can be shown, while maintaining real time capability. Furthermore, the structural fatigues of the tower and the platform are decreased.
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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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    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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    LIDAR assisted collective pitch control
    (2011) Schlipf, David; Bossanyi, Ervin; Carcangiu, Carlo Enrico; Fischer, Tim; Maul, Timo; Rossetti, Michele
    Nacelle based pulsed LIDAR (Light detection and ranging) systems provide preview information of wind disturbances at various distances in front of wind turbines. In previous work it has been shown that this information can be used to improve the speed regulation of wind turbines by a look-ahead update to the collective pitch control, which indicates load reduction of tower and blades. In the scope of the UpWind project a first fatigue and extreme load analysis has been done to concretize the improvement of look-ahead collective pitch control using LIDAR.
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    Control co-design optimization of floating offshore wind turbines with tuned liquid multi-column dampers
    (2024) Yu, Wei; Zhou, Sheng Tao; Lemmer, Frank; Cheng, Po Wen
    The technical progress in the development and industrialization of floating offshore wind turbines (FOWTs) over the past decade has been significant. Yet, the higher levelized cost of energy (LCOE) of FOWTs compared to onshore wind turbines is still limiting the market share. One of the reasons for this is the larger motions and loads caused by the rough environmental excitations. Many prototype projects tend to employ more conservative substructure designs to meet the requirements for motion dynamics and structural safety. Another challenge lies in the multidisciplinary nature of a FOWT system, which consists of several strongly coupled subsystems. If these subsystems cannot work in synergy, the overall system performance may not be optimized. Previous research has shown that a well-designed blade pitch controller is able to reduce the motions and structural loads of FOWTs. Nevertheless, due to the negative aerodynamic damping effect, improvement in the performance by tuning the controller is limited. One of the solutions is adding tuned liquid multi-column dampers (TLMCDs), meaning that there is a structural solution to mitigate this limiting factor for the controller performance. It has been found that the additional damping, provided by TLMCDs, is able to improve the platform pitch stability, which allows a larger blade pitch controller bandwidth and thus a better dynamic response. However, if a TLMCD is not designed with the whole FOWT system dynamics taken into account, it may even deteriorate the overall performance. Essentially, an integrated optimization of these subsystems is needed. For this paper, we develop a control co-design optimization framework for FOWTs installed with TLMCDs. Using the multi-objective optimizer non-dominated sorting genetic algorithm II (NSGA-II), the objective is to optimize the platform, the blade pitch controller, and the TLMCD simultaneously. Five free variables characterizing these subsystems are selected, and the objective function includes the FOWT's volume of displaced water (displacement) and several motion and load indicators. Instead of searching for a unique optimal design, an optimal Pareto surface of the defined objectives is determined. It has been found that the optimization is able to improve the dynamic performance of the FOWT, which is quantified by motions and loads, when the displacement remains similar. On the other hand, if motions and loads are constant, the displacement of the FOWT can be reduced, which is an important indication of lower manufacturing, transportation, and installation costs. In conclusion, this work demonstrates the potential of advanced technologies such as TLMCDs to advance FOWTs for commercial competitiveness.
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    Quantification of amplitude modulation of wind turbine emissions from acoustic and ground motion recordings
    (2023) Blumendeller, Esther; Gaßner, Laura; Müller, Florian J. Y.; Pohl, Johannes; Hübner, Gundula; Ritter, Joachim; Cheng, Po Wen
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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.