15 Fakultätsübergreifend / Sonstige Einrichtung

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/16

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Institute: search.filters.UBSInstitut.Institut für FlugzeugbauAuthor: search.filters.author.Haizmann, Florian

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Now showing 1 - 4 of 4
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    Detection of wind evolution and lidar trajectory optimization for lidar-assisted wind turbine control
    (2015) Schlipf, David; Haizmann, Florian; Cosack, Nicolai; Siebers, Tom; Cheng, Po Wen
    In 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.
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    An adaptive data processing technique for lidar-assisted control to bridge the gap between lidar systems and wind turbines
    (2015) Schlipf, David; Fleming, Paul; Raach, Steffen; Scholbrock, Andrew; Haizmann, Florian; Krishnamurthy, Raghu; Boquet, Matthieu; Cheng, Po Wen
    This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited or can even result in harmful control action. An online analysis of the lidar and turbine data is necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross-correlation to determine the time shift between both signals. Further, we present initial results from an ongoing campaign in which this system was employed for providing lidar preview for feedforward pitch control.
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    Field testing of feedforward collective pitch control on the CART2 using a nacelle-based lidar scanner
    (2012) Schlipf, David; Fleming, Paul; Haizmann, Florian; Scholbrock, Andrew; Hofsäß, Martin; Wright, Alan; Cheng, Po Wen
    This work presents the first results from a field test to proof the concept of LIDAR assisted collective pitch control using a scanning LIDAR device installed on the nacelle of a research turbine. The purpose of the campaign was to show that a reduction of rotor speed variation is feasible with a feedforward update without changing the feedback controller. Although only a small amount of data could be collected, positive effects can be observed not only on the rotor speed but also on tower, blade and shaft loads in the case that the correlation of the wind preview and the turbine reaction is taken into account.
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    Model based wind vector field reconstruction from lidar data
    (2012) Schlipf, David; Rettenmeier, Andreas; Haizmann, Florian; Hofsäß, Martin; Courtney, Mike; Cheng, Po Wen
    In recent years lidar technology found its way into wind energy for resource assessment and control. For both fields of application it is crucial to reconstruct the wind field from the limited information provided by a lidar system. For lidar assisted wind turbine control model based wind field reconstruction is used to obtain signals from wind characteristics such as wind speed, direction and shears in a high temporal resolution. This work shows how these methods can be used for lidar based wind resource assessment in complex situations, where high accuracy is important, but cannot be archived by conventional technique. The reconstruction is validated for ground based lidar systems with measurement data and for floating lidar systems with detailed simulations.