06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
Browse
33 results
Search Results
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 IEA Wind Task 32: Wind Lidar : identifying and mitigating barriers to the adoption of wind lidar(2018) Clifton, Andrew; Clive, Peter; Gottschall, Julia; Schlipf, David; Simley, Eric; Simmons, Luke; Stein, Detlef; Trabucchi, Davide; Vasiljevic, Nikola; Würth, InesIEA Wind Task 32 exists to identify and mitigate barriers to the adoption of lidar for wind energy applications. It leverages ongoing international research and development activities in academia and industry to investigate site assessment, power performance testing, controls and loads, and complex flows. Since its initiation in 2011, Task 32 has been responsible for several recommended practices and expert reports that have contributed to the adoption of ground-based, nacelle-based, and floating lidar by the wind industry. Future challenges include the development of lidar uncertainty models, best practices for data management, and developing community-based tools for data analysis, planning of lidar measurements and lidar configuration. This paper describes the barriers that Task 32 identified to the deployment of wind lidar in each of these application areas, and the steps that have been taken to confirm or mitigate the barriers. Task 32 will continue to be a meeting point for the international wind lidar community until at least 2020 and welcomes old and new participants.Item Open Access Optimization of floating offshore wind turbine platforms with a self-tuning controller(2017) Lemmer, Frank; Müller, Kolja; Yu, Wei; Schlipf, David; Cheng, Po WenThe 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.Item Open Access Nonlinear model predictive control of floating wind turbines(2013) Schlipf, David; Sandner, Frank; Raach, Steffen; Matha, Denis; Cheng, Po WenIn 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.Item Open Access Nonlinear model predictive control of floating wind turbines with individual pitch control(2014) Raach, Steffen; Schlipf, David; Sandner, Frank; Matha, Denis; Cheng, Po WenIn 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.Item Open Access Flatness-based feedforward control of wind turbines using Lidar(2014) Schlipf, David; Cheng, Po WenCurrent 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.Item Open Access Realistic simulations of extreme load cases with lidar-based feedforward control(2017) Hagemann, Tim; Haizmann, Florian; Schlipf, David; Cheng, Po WenThis 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.Item Open Access Lidar-based wake tracking for closed-loop wind farm control(2017) Raach, Steffen; Schlipf, David; Cheng, Po WenThis work presents two advancements towards closed-loop wake redirection of a wind turbine. First, a model-based wake-tracking approach is presented, which uses a nacelle-based lidar system facing downwind to obtain information about the wake. The method uses a reduced-order wake model to track the wake. The wake tracking is demonstrated with lidar measurement data from an offshore campaign and with simulated lidar data from a simulation with the Simulator fOr Wind Farm Applications (SOWFA). Second, a controller for closed-loop wake steering is presented. It uses the wake-tracking information to set the yaw actuator of the wind turbine to redirect the wake to a desired position. Altogether, the two approaches enable a closed-loop wake redirection.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 Statistical load estimation using a nacelle-based lidar system(2010) Bischoff, Oliver; Hofsäß, Martin; Rettenmeier, Andreas; Schlipf, David; Siegmeier, BjörnThe 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.