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.KonferenzbeitragStart date: 2020

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    Messungen im Bereich eines Windparks mit Fokus auf tief- und niederfrequente Schallemissionen und -immissionen
    (2022) Blumendeller, Esther; Gaßner, Laura; Müller, Florian; Wigger, Maayen; Berlinger, Philipp; Cheng, Po Wen
    Die Nutzung von Windenergie wird einen entscheidenden Anteil am erneuerbaren Energiemix der Zukunft haben. Während der Stromgewinnung geben Windenergieanlagen (WEA) Schall und Erschütterungen (seismische Wellen) in die Umgebung ab, vor allem im tieffrequenten Bereich. Im Zuge des interdisziplinären Verbundprojektes Inter-Wind werden akustische Messungen zur Unterstützung psychologischer Fragebögen, kombiniert mit seismischen und meteorologischen Messungen an Windparks auf der Schwäbischen Alb durchgeführt. Ziel des Projektes ist es, die Gründe für Belästigung der Anwohner in Zusammenhang mit den Immissionen der WEA zu verstehen. Hierbei liegt der Fokus auf dem tieffrequenten (20-200 Hz) und niederfrequenten (1-20 Hz) Bereich. Akustische und seismische Messungen wurden an einem Windpark auf der Schwäbischen Alb, mit drei WEA des Typs GE 2.75-120 durchgeführt. Parallel dazu konnten Anwohner Belästigungszeiträume über eine Geräuschmelde-App dokumentieren. In diesem Beitrag wird die Umsetzung einer interdisziplinären Messkampagne im Bereich des Tegelberg Windparks und eines Wohngebäudes in Tallage in ca. 1 km Entfernung zum Windpark beschrieben. Schließlich werden erste Ergebnisse der akustischen Messungen und interdisziplinären Untersuchung vorgestellt und diskutiert.
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    FlexDyn - a new OpenFAST structural dynamics module for a general, user defined wind turbine topology
    (2021) Lemmer, Frank; Pérez Brovia, Santiago; Skandali, Danai; Raach, Steffen
    In the present work, FlexDyn, a new structural dynamics module for the OpenFAST framework is developed. FlexDyn can generate structural equations of motion through a formalism, given user-defined rigid and elastic bodies and associated Degrees of Freedom (DOFs). The Newton-Euler formalism uses beam models with shape functions for a reduced-order representation in the same way as ElastoDyn of OpenFAST. The equations of motion are formulated in minimal coordinates, equally to ElastoDyn. FlexDyn is fully integrated into the OpenFAST framework with a coupling to AeroDyn and the new SubDyn module for FE representations of floating substructures (Jonkman, et al., 2020), among others. The formalism was previously implemented and verified in the low-order aero-hydro-servo-elastic code SLOW (Lemmer, et al., 2020). The objective of the presentation is to show the methodology of the formalized generation of equations of motion and first results of the new FlexDyn module for OpenFAST. The use case is an improved aero-elastic model, which includes the torsional DOF of the blades. The torsional DOF is not included in the ElastoDyn module but can potentially contribute to the motion and load response of the blades. The fidelity level of this use case of FlexDyn is higher than that of ElastoDyn but still below that of BeamDyn, which is a full FE representation of the blades. For this reason, the computational performance is still in the range of ElastoDyn, taking advantage of the order reduction.
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    Multi-variable feedforward control for floating wind turbines using lidar
    (2020) Schlipf, David; Lemmer, Frank; Raach, Steffen
    In this work a multi-variable feedforward controller for floating wind turbines is presented. The feedforward controller provides a pitch rate and a torque update to a conventional feedback controller based on a wind speed preview. A 10 MW reference wind turbine is used on a semi submersible floating platform to study the potential of the controller. An open-source simulation tool is extended with an realistic lidar simulator and the lidar data processing, feedforward controller, and feedback controller are implemented in modular setup. The lidar measurements are fully motion compensated and combined to provide a preview of the rotor-effective wind speed to the controller. The feedforward controller is designed to minimize structural loads and to decrease the platform pitch motion. In verification and simulation studies the concept is demonstrated and the multi-variable feedforward controller shows a promising improvement in speed regulation and load reduction on the floating wind turbine.
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    Advances on reduced-order modeling of floating offshore wind turbines
    (2021) Lemmer, Frank; Yu, Wei; Steinacker, Heiner; Skandali, Danai; Raach, Steffen
    Aero-hydro-servo-elastic modeling of Floating Offshore Wind Turbines (FOWTs) is a key component in the design process of various components of the system. Different approaches to order reduction have been investigated with the aim of improving structural design, manufacturing, transport and installation, but also the dynamic behavior, which is largely affected by the blade pitch controller. The present work builds on previous works on the SLOW (Simplified Low-Order Wind Turbine) code, which has already been used for the above purposes, including controller design. While the previous rigid rotor model gives good controllers in most cases, we investigate in the present work the question if aero-elastic effects in the design model can improve advanced controllers. The SLOW model is extended for the flapwise bending and coupled to NREL's AeroDyn, linearized and verified with the OlavOlsen OO-Star Wind Floater Semi 10MW public FOWT model. The results show that the nonlinear and linear reduced-order SLOW models agree well against OpenFAST. The state-feedback Linear Quadratic Regulator (LQR) applied with the same weight functions to both models, the old actuator disk, and the new aero-elastic model shows that the LQR becomes more sensitive to nonlinear excitation and that the state feedback matrix is significantly different, which has an effect on the performance and potentially also on the robustness. Thus modeling uncertainties might even be more critical for the LQR of the higher-fidelity model.