Browsing by Author "Cheng, Po Wen (Prof. Dr.)"

Now showing 1 - 15 of 15

Open Access
Analysis and application of lidar inflow measurements for floating offshore wind turbines
(2025) Gräfe, Moritz Johann; Cheng, Po Wen (Prof. Dr.)
Open Access
Assessment of structural loads in wind farms under consideration of wake redirection control
(2024) Kretschmer, Matthias; Cheng, Po Wen (Prof. Dr.)
Wind farm control enables the operation of wind farms in a collective optimum that considers all turbines instead of operating the individual wind turbines in their local optima. The development of new wind farm control techniques requires knowledge in various disciplines that include wind turbine engineering (control design and implementation, structural and aerodynamic design, load assessment and validation), multidisciplinary optimisation, wind resource modelling and atmospheric boundary layer modelling connected with the modelling of wakes. This thesis covers many of the aforementioned disciplines in order to investigate the wake redirection control concept as one option for wind farm control in detail. For the numerical assessment, the aeroelastic simulation tool FAST.Farm is utilised. An adequate setup of the tool is developed to allow the investigation of various realistic operating conditions including different atmospheric stabilities. In addition, FAST.Farm is improved by implementing a model to include the wake-added small-scale turbulence. FAST.Farm is then calibrated against high-fidelity large eddy simulations and validated by using measurement data from the alpha ventus wind farm. Overall, good agreement between simulations and measurements is achieved for the structural loads in terms of statistical results and frequency response at the tower-base and blade-root. The inclusion of wake-added turbulence is crucial to avoid underestimation of the turbulence in the wake and consequently the loads. This is especially relevant in stable atmospheric conditions, where the ambient turbulence intensity is low and the meandering of the wake is weak. An extensive investigation of the wake redirection control concept and its consequences on the structural loads is performed in a simulation study with the validated tool FAST.Farm. For a turbine in free-stream conditions, the fatigue loads at different turbine components are analysed, with changing atmospheric conditions and yaw misalignment angles. The largest effects of yaw misalignment on the load variations are found for stable atmospheric conditions with strong vertical wind shear and low turbulence intensity. In contrast, the influence of yaw misalignment on the fatigue loads becomes less important in unstable atmospheric stability with low vertical wind shear and high turbulence intensity. The investigation is extended for a turbine that is subjected to waked inflow conditions. Especially in partial wake situations, the load distributions differ significantly from free-stream conditions. A directional dependency of the loads is found with respect to the lateral wake offset: The loads tend to be higher for negative lateral wake offsets compared to the loads from the same positive lateral wake offsets, because of higher load amplitudes over one rotor revolution. The gained knowledge is finally applied in the derivation of optimal operation strategies by using the wake redirection control approach for exemplary wind farm configurations and changing environmental conditions. The resulting optimal operation strategies are assessed by using aeroelastic simulations in FAST.Farm. The long-term evaluation suggests that the annual energy production (AEP) of the considered turbine array setups can be increased compared to the baseline scenario without wind farm control, when the main objective is set to power maximisation while the fatigue loads at the turbines are not or equally weighted. Consequently, the strategies that focus on minimising the fatigue loads result into less AEP compared to the baseline strategy. The consideration of fatigue loads in the optimisation of operation strategies is realised with an efficient surrogate model. With this approach, strategies are derived that are able to reduce the fatigue loads at specific components significantly.
Open Access
Design, simulation and optimization of shared mooring line configurations for floating wind farms
(2025) Pan, Qi; Cheng, Po Wen (Prof. Dr.)
This study establishes a comprehensive framework to address key challenges in the design, simulation, and optimization of shared line configurations, providing insights for their evaluation and implementation in floating wind farms.
Open Access
Development of a flying wind measurement system for collective operation
(2020) Molter, Christian; Cheng, Po Wen (Prof. Dr.)
Using a multirotor aircraft for wind measurements results in a novel add-on to conventional measurement technologies because outdoor measurements at several arbitrary locations in three-dimensional space at high temporal and spatial resolution have not been possible before. If such a swarm measurement is to be realized with a group of conventional multirotor aircraft, a number of potential problems exist. To cope with these problems, the present work has been divided into two parts. On the one hand, the underlying effects have been investigated by analytical calculations, simulations and experiments to gain a deeper understanding and derive guidelines and procedures regarding flying wind measurements, as well as multirotor design in general. On the other hand a purpose designed aircraft has been developed most suited for the measurement task. Together with a probe manufacturer a custom flow measurement probe was developed. This design combines the robustness of a Prandtl tube with the high temporal resolution and directional sensitivity of a triple hot wire probe. The data acquisition system for the probe was also customized and connected to the autopilot in order to make live-readings and automatic alignments of the aircraft with the wind direction possible. Finally, to address the problem of vibrations a modal analysis and frequency tuning of the measurement boom has been conducted. The flight and measurement performance of the first prototype aircraft could be demonstrated with great success. To characterize the lower end of the measurable wind speed range free flights in a gust wind tunnel have been undertaken, while the "real life" measurement performance was shown in a field test next to a met mast at wind speeds up to 13 m/s.
Open Access
Experimental investigation of low-frequency sound and infrasound induced by onshore wind turbines
(2024) Blumendeller, Esther; Cheng, Po Wen (Prof. Dr.)
Climate change has a global impact and is increasingly affecting our environment. This is driving the continuous expansion of renewable energies, with wind energy playing a major role. As wind energy becomes more widespread, an increasing number of people will live near wind turbines in complex terrain. In such scenarios, wind turbines are often positioned at elevated locations, while residents live in valleys. In complex terrain, such as a steep escarpment, local turbulence, wind speed, and direction are strongly influenced by topography, contributing to the complexity of sound propagation or impacts the background noise situation in valleys, for example, due to shielding effects. The operation of wind turbines is associated with both visual and sound-related impact, with sound being generated at various frequencies. There is a growing interest in low-frequency sound and infrasound, characterized by long wavelengths that propagate over considerable distances without significant attenuation. This is in contrast to higher-frequency sound, and might increase the impact of wind turbine sound at residential areas located several hundred meters or a few kilometers away from the wind farm. In the context of complex terrain, this work investigates wind turbines in complex terrain as sources of low-frequency sound and infrasound. The investigations on characterization of sound generation and propagation are based on measurements in the vicinity of two wind farms. Measurements were conducted within four measurement campaigns at two wind farms located close to an escarpment at the Swabian Alb in Southern Germany over a period of about nine month. Acoustic data was obtained in the proximity of the wind turbines and at residential buildings in 1–1.7km distance to the wind farms in municipalities located within a valley. Besides acoustic measurements including the infrasonic frequency range, a comprehensive data set with ground motion data, wind turbine operating data, meteorological data and data from a noise reporting app supports the investigation. Two aspects require analysis: Firstly, the aspect of generation and propagation of wind turbine low-frequency sound and infrasound in complex terrain, and secondly, the relation with annoyance. Results show that sounds within the infrasonic range assigned to the blade passage at the tower are transmitted through the air over distances of 1 km. Low-frequency sounds were found to be amplitude-modulated and were investigated as amplitude modulation. Infrasound and amplitude modulation occurrences were more likely during morning, evening and night hours and during atmospheric conditions with positive lapse rate, vertical wind shear and low turbulence intensity. The occurrence of both infrasound and amplitude modulation was typically observed during rated rotational speed but below-rated power. To allow predictions, a standard prediction method was extended to include the lowfrequency sound and infrasound range and adapted to the measurement data in order to apply it to complex terrain. The sound level difference of the measured data aligns well with the predictions within the frequency range of 8 Hz and 250 Hz. Investigations regarding outdoor-to-indoor sound reductions showed influences from structural resonances and room modes, which depend on the characteristics of the building and the specific room under investigation. Combining acoustic measurements with annoyance reports showed that rated wind turbine operation appears to be a contributing factor in annoyance ratings obtained through a noise reporting app, ranging from “somewhat” to “very” levels. Furthermore, the analysis indicates that varying levels of annoyance at a distance of 1km from the wind farm, both outside and inside buildings, do not correspond to significant differences in the averaged and A-weighted sound pressure levels. Overall, this work contributes to a better understanding of the low-frequency sound and infrasound generated from wind turbines and provides insight into the sound characteristics of measured wind turbine sound at residential locations in complex terrains.
Open Access
High-fidelity simulation and analysis of a floating offshore wind turbine under extreme wave and wind conditions
(2022) Borisade, Friedemann; Cheng, Po Wen (Prof. Dr.)
A high-fidelity simulation environment is developed based on a coupled methodology of MBS and CFD solvers. The methodology provides an integrated analysis of floating offshore wind turbines with consideration of aero- and hydrodynamics, structural dynamics as well as mooring and control system. A numerical wave tank is build in CFD. Experimental data from a wave tank model test, conducted in the course of the EU FP7 FLOATGEN project, are used to validate the simulation approach. The MBS model of a generic 2.2 MW wind turbine is simulated under extreme wave and wind conditions using a deterministic, phase-focused wave group based on representative metocean conditions with 50-year return period. A steady extreme wind speed model is used for computation of aerodynamic loads on the flexible rotor using BEM theory and wind drag forces on the flexible tower. Platform surge is highly excited by extreme wave conditions and significant wave run-up at the transition piece is observed. However, maximum inclinations and accelerations of the nacelle and tower are still within acceptable survival design margins of a barge-type floating substructure. The results demonstrate that the developed high-fidelity MBS-CFD simulation environment can fill the gap between engineering models and experiments for the design of floating offshore wind turbines. The methodology provides results, which cannot be obtained from other simulation techniques, such as wave run-up and pressure distributions under extreme conditions.
Open Access
Improved modeling of lidar wind preview for wind turbine control
(2023) Guo, Feng; Cheng, Po Wen (Prof. Dr.)
Lidar has been used in the wind energy field for decades. Most of the time, it was mainly used for wind resource assessments of potential wind farms. In recent years, the cost of lidar systems has decreased significantly, and the applications of lidar have become increasingly diverse. In some cases where it is more expensive to erect meteorological mast towers, such as offshore wind farm development, lidar has become the preferred resource assessment choice. In addition to resource assessment, lidar has attracted extensive research interest in wind turbine control, power performance characterization, wind power prediction, and wind farm control. In terms of lidar-assisted control, this technology has been proven to reduce wind turbine loads, rotor speed variations, and power fluctuations. In recent years, lidar-assisted wind turbine control has been applied to commercial projects. Wind turbines operate mainly in atmospheric turbulence, where wind speeds are highly random and fluctuating. The wind rotates the turbine to generate electricity while also imposing fatigue loads. Traditional wind turbine control only relies on feedback control, which adjusts the blade pitch angles and the generator torque by measuring changes in the rotational speed of the turbine. This control effect is achieved after the turbulent wind disturbance has already acted on the wind turbine and it is lagging. Differently, lidar-assisted control uses the wind preview provided by nacelle- or spinner-lidars to achieve feedforward control. For example, when the wind speed changes, the lidar can sense that and inform the pitch control system to achieve an earlier pitch adjustment. Some key features of nacelle lidar measurements make it necessary to process the lidar measurement before it can be used for turbine control. For instance, the lidar measurement is the projection of the three-dimensional wind velocity vector onto the lidar beam direction, but the turbine rotor is mainly interacting with the axial component in the velocity vector. In addition, the lidar system provides only limited measurements of the upstream position while the turbine rotor interacts with the downstream turbulence through its three blades. Usually, differences in turbulence at upstream and rotor positions are described as wind evolution. Further, the lidar measurement can be unavailable due to blade blockage or special weather patterns. Therefore, a lidar preview quality study needs to be performed to determine the usable part of the wind preview provided by the lidar. A filter design is necessary to filter out uncorrelated information in the lidar wind preview. In actual operation, wind turbines suffer from different atmospheric stability conditions. In different atmospheric stability conditions, the spectrum and coherence of the turbulent wind can vary. Because of the limited measurement at upstream positions, lidar preview is highly linked to the spatial coherence of turbulence. Thus far, it is still unclear whether the variation of the turbulence characteristics will have an impact on the lidar preview quality and the benefits of lidar-assisted control. Although there are already commercial use cases for lidar-assisted control, the existing lidar-assisted control simulation environment does not fully cover the characteristics of lidar measurements discussed above. Therefore, the main objective of this thesis is to improve the lidar wind preview modeling and assess the benefits of lidar-assisted control using the improved modeling. First, the improvement is achieved by incorporating the wind evolution phenomenon into conventional three-dimensional turbulence models: the Mann and Kaimal models, resulting in four-dimensional turbulence models. The performances of these two extended models in predicting turbulence spectra and spatial coherences are evaluated using measurements from a pulsed lidar and a meteorology mast. Furthermore, the analytical models which represent the correlation between the lidar-previewed rotor effective wind speed and the rotor effective wind speed at the rotor position, are derived based on the extended turbulence models. Spectra and coherences of turbulence in different atmospheric stabilities are summarized, and their impacts on lidar preview qualities are investigated. A preliminary study on whether the upstream wind turbine wake affects the lidar preview of a downwind wind turbine is also conducted. Moreover, a realistic lidar module is updated in the aeroelastic simulation tool, which allows for studying the impact of unavailable lidar data on lidar wind preview quality. Through simulations using realistic data availability, this study indicates that the blade blockage and low data availability event have negligible impacts on the lidar preview quality. Finally, this thesis evaluates the benefits of lidar-assisted control under various turbulence characteristics representative of different atmospheric stabilities using the updated aeroelastic simulation tool. This study exhibits that the benefits of lidar-assisted control are related to the mean wind speed, turbulence spectrum, turbulence spatial coherence, and used turbulence models. For the NREL 5.0 MW turbine and a four-beam lidar, the benefits of lidar-assisted control are primarily reductions in rotor speed variation, power fluctuation, and tower-base bending load. The benefits are observed in all three investigated stabilities: unstable, neutral, and stable.
Open Access
Increase in annual energy production through passive self-adjusting layouts of floating wind farms
(2024) Mahfouz, Mohammad Youssef; Cheng, Po Wen (Prof. Dr.)
Wind energy is essential for transitioning to sustainable energy sources. To harness its full potential, it is crucial to access locations with abundant wind resources. Interestingly, 60% to 80% of the most promising wind energy sites are located in deep waters offshore. These sites can only be utilized using offshore wind turbines. Harnessing wind energy in deep waters not only taps into rich wind resources but also aims to boost the efficiency of wind farms by reducing energy losses. A significant source of these losses is known as wake losses. The power generated by a wind turbine depends heavily on the wind speed hitting its rotor, specifically, it is proportional to the cube of this wind speed. As wind passes through a turbine, the blades extract energy, resulting in the wind flow, leaving the turbine with less energy, lower wind speed, and higher turbulence. When this lower-energy wind reaches another turbine downwind, the second turbine receives less wind speed and, therefore, produces less energy compared to the turbine upwind. This difference in energy production due to the shadowing effect of the first turbine is called wake losses. This research introduces a new method to reduce wake losses in floating wind farms. The approach involves passively relocating the floating offshore wind turbines to optimize their positions relative to each other. Unlike fixed turbines, floating offshore wind turbines are secured to the seabed with mooring lines, which allow them to move within a certain range. The extent of this movement depends on the design of the mooring system, as well as the wind speed and direction. For a given mooring system, the displacement of the turbine changes with varying wind conditions. Thus, by smartly designing the mooring system, we can control the movement of floating turbines to minimize wake losses. This study explores the concept of designing customized mooring systems to create a floating wind farm layout that can adjust itself passively and reduce wake losses. These self-adjusting layouts should not only reduce wake losses but also be cost-effective. The design must ensure that the new mooring systems' costs are lower than current state-of-the-art mooring systems. Additionally, the fatigue and extreme loads on the turbine components mustn't increase due to the larger displacements of the turbines. The research findings show that a passively self-adjusting wind farm layout increases a floating wind farm's annual energy production (AEP). Importantly, this improvement is accomplished without increasing the extreme and fatigue loads on the turbines, maintaining the safety and reliability of the FOWTs. For a layout of nine turbines, the AEP was increased by 1.5%, and the mooring system costs were decreased by 4%. For the Horns Rev 1 layout in the North Sea with 80 turbines, the AEP increased by 1%, and the costs decreased by 6%. These results indicate significant potential for scalable and cost-effective improvements in floating offshore wind energy production. In summary, this work presents a promising approach to enhancing the efficiency of floating wind farms by smartly designing mooring systems that allow turbines to adjust their positions passively. This innovation not only taps into abundant offshore wind resources but also enhances energy production and reduces costs, paving the way for more sustainable and efficient wind energy solutions.
Open Access
Lidar-assisted control concepts for wind turbines
(2016) Schlipf, David; Cheng, Po Wen (Prof. Dr.)
Current advances in lidar technology provide opportunities to take a fresh look at wind turbine control. The wind is not only the main energy source but also the major disturbance to the control system. Thus, knowledge of the incoming wind is valuable information for optimizing energy production and reducing structural loads. Due to the measurement principles and the complexity of the wind, the disturbance cannot be measured perfectly. This forms a challenging task for estimation and control. Within this thesis project, research has been carried out in the field of predictive control for onshore wind turbines. The thesis presents concepts of lidar-assisted control to reduce the structural loads and also to increase the energy yield of wind turbines, both of which make wind energy more competitive. The key challenges have not only been to develop appropriate feedforward control methods applicable to an industrial feedback controller, but also to investigate turbulence characteristics and to derive lidar measurements techniques to provide a usable preview signal. The combination of these findings made a proof-of-concept possible on two research wind turbines using a commercial and an adapted lidar system.
Open Access
Lidar-assisted wake redirection control
(2019) Raach, Steffen; Cheng, Po Wen (Prof. Dr.)
Wind energy has developed to a competitive energy source and is intended to play an important role in the world-wide sustainable energy supply. The size of wind turbines has tremendously increased and turbines have been clustered to wind farms in order to share infrastructure and moreover reach energy production capacities of conventional power plants. However, the operation of wind turbines in a wind farm hasn't changed compared to single turbine operation. Possible interactions between wind turbines through the wind are not considered in the operation strategy of the turbines. The wake of a wind turbine can negatively influence the operation of a downwind turbine because the wind speed is reduced and the turbulence intensity is increased in the wake. Currently, each wind turbine is maximizing its power output independently of the other wind turbines. In a total consideration this may result in a suboptimal power output due to the interaction of wind turbines. In the case a wake impinges a second wind turbine, that turbine produces less power and the structural loads may increase. Both effects negatively impact the operation of the wind turbine and therefore it makes sense to avoid wake interactions. This task demands new wind park control concepts which take wind turbine interactions into account. In current research activities the wind farm is treated as the total system. Different investigations in wind farm control have identified two promising operation concepts: axial induction control and wake redirection control. Whereas the concept of induction control tries to minimize the impact of wakes on other wind turbines, the basic idea of wake redirection control is to redirect the wake of a wind turbine by yawing the wind turbine and therefore forcing a misalignment to the wind direction. Using this technique, interactions between wind turbines can be minimized. The current concept is based on an open-loop methodology in which a reduced-order wake model is used to pre-calculate the optimal yaw angles. This results in two disadvantages: The uncertainty which a simplified model introduces and the missing possibility to react to disturbances. This work introduces the concept of lidar-based closed-loop wake redirection control which can adapt to uncertainties and react on disturbances. Therefore it extends the concept of wake redirection control with a new closed-loop methodology. This work contributes various aspects to enable a lidar-based closed-loop wake redirection control. It first presents the general concept. Then it is separated in two subtasks: the measurement and the control tasks. This separation helps to focus on the specific questions of each task. First the measurement task is addressed and solutions are provided to process lidar measurement data to a useful signal for the wake redirection controller. Different methodologies are presented to track the wake position using lidar measurement data and the concept of model-based wake tracking is described in detail. Afterwards the control task is considered. Three different controller synthesis concepts are applied to wake redirection and controllers are synthesized. The different controllers are analyzed and the performances are assessed. Then the controllers are verified in different simulation tools. Mainly simulations are performed with a medium-fidelity computational fluid dynamics simulation tool. In addition the concept is implemented in a Large-Eddy simulation tool to demonstrate the adaption to disturbances and model uncertainties. Altogether the work introduces lidar-based closed-loop wake redirection control. It demonstrates the feasibility of the concept as well as the adaptivity of the controller to model uncertainties and disturbances. The different aspects of the concept are considered and methodologies for wake position estimation are provided and controllers are designed. Finally, recommendations are given to realize the concept in reality, and open questions are highlighted which require deeper investigations.
Open Access
Low-order modeling, controller design and optimization of floating offshore wind turbines
(2018) Lemmer, Frank; Cheng, Po Wen (Prof. Dr.)
Ongoing demonstration projects prove the technical feasibility of offshore wind turbines on floating foundations, moored by anchor lines. The present work starts with the derivation of a tailored numerical model, which represents not more than the most relevant effects to simulate the system dynamics, observed from experiments, including aerodynamics, hydrodynamics, structural dynamics and the control system. This provides the basis for an integrated design study to take floating wind turbines to the next stage of development. It is shown that the integrated design yields systems with a smooth dynamic behavior in harsh wind and wave conditions.
Open Access
Minute-scale forecasting of wind power using long-range lidar data
(2022) Würth, Ines; Cheng, Po Wen (Prof. Dr.)
With the introduction of renewable energies, the power grid has transformed from a centralised to a decentralised system. To balance the supply and demand of power in the energy grid at all times in spite of the volatile nature of wind and solar power, grid operators have to rely on accurate forecasts. However, state of the art wind power forecasting methods are not able to forecast changes of power in the minute-scale accurately. Therefore new methods are needed. This thesis investigates the use of a long-range lidar to forecast wind power on the minute-scale. To that aim, two measurement campaigns were carried out. One was an onshore campaign, where the lidar was installed fixed on a radio tower next to a turbine that a forecast was made for. The second was an offshore campaign where the lidar was installed on top of the nacelle of a wind turbine. Both campaigns lasted over several months and the wind speed was measured in several kilometers in front of the turbine. During this time the turbine`s own data system also recorded the 10-minute average power from the turbine. In this thesis, a wind power forecast process is established. Lidar data is transformed from radial velocity to filtered horizontal wind speed and wind direction. The wind field information is then propagated to the wind turbine with an advection model based on Taylor's hypothesis. The forecasted wind speed at the turbine is then transformed into a forecasted power with the help of the power curve of the turbine. To account for the uncertainty in the wind speed and power forecast, probabilistic forecast methods are applied. The results show that lidar-based forecasts at the offshore site are accurate in a forecast horizon up to ten minutes and outperform the benchmark forecast method persistence. Longer forecast horizons are biased because only small wind speeds measured further away from the wind turbine arrive with a delay of more than ten minutes. At the onshore site, persistence outperforms the lidar-based method in all forecast horizons, includinig the forecast horizon up to 10 minutes. The reason is that the Taylor based advection model does not model the actual propagation at the complex onshore site well enough. During ramp events, the lidar-based forecast demonstrates its strength: information from the wind speed measured a few kilometers in front of the turbine allows us to forecast changes of power. In comparison, persistence only uses old information and therefore cannot forecast any future changes. It is concluded that the added value of using a lidar for minute-scale forecasts lies in forecasting changes of power. As wind ramps are potentially critical to the grid stability, or can affect the cost of balancing the power system if they are not forecast well, using lidars at wind farms to improve the power forecast is advised. However, challenges to the implementation of lidar-based forecasts remain. Lidar measurements depend on the aerosol content in the air and therefore the availability of the measurements for a forecast is not guaranteed. A fallback solution is needed such as statistical models or numerical weather prediction. To achieve forecast horizons of more than 10 minutes, the lidar measurement range needs to be extended beyond 10 kilometers. And to establish lidars as a state-of-the-art forecasting tool, standards are needed, which could be enabled by groups such as the IEA Wind community. Wind lidar data coupled with propagation models and power curves has fundamental advantages for minute-scale wind power forecasting. Although this thesis has shown that current approaches may not be perfect, the rapid pace of wind lidar technology development, the increasing number of users, and the growing network of third party service providers, suggests that wind lidar is the future of minute-scale wind power forecasting.
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Modeling, testing and application of tuned liquid multi-column dampers for floating offshore wind turbines
(2024) Yu, Wei; Cheng, Po Wen (Prof. Dr.)
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Modelling and analysis of electro-mechanical interactions in wind turbines
(2024) Lüdecke, Fiona Dominique; Cheng, Po Wen (Prof. Dr.)
The contribution of wind energy to the energy transition is steadily increasing. This growing contribution is driven by two aspects: the construction of new turbines and the increase in turbine size. In particular, for offshore sites, the nominal power of new turbines is now up to 16 MW and rising. Two main drive-train concepts are used, the geared and the direct-drive. Direct-drives, the focus of this work, have a characteristically low speed in order to limit the blades' tip speed. This results in large generator diameters, which have reached around 10 m. Scaling laws show that structural support mass grows faster than active mass, contributing to power generation. Therefore, new design methods for mass reduction are desired. The generator design is optimised based on given input loads and must maintain the air gap between the rotor and stator at all times. Typically, this is achieved by very high main bearing and generator support structure stiffness requirements, limiting mass reduction potential. In this work, it is assumed that designing wind turbines based on component optimisation does not ensure the best system design. However, moving to a more system-oriented approach requires new, holistic modelling techniques to simulate the wind turbine system, including electromagnetic forces from the generator. The required system model is derived in this thesis by adding a radial degree of freedom to the state-of-the-art wind turbine model. Two generator models of different fidelity are coupled to the wind turbine model, an analytical and a finite element model. Influences of the model adaptations on the system behaviour are identified. Structural component interactions are analysed and the effects of modelling on interactions with the aerodynamic solver and controller are investigated. The results show that lower system modes can be affected in their natural frequency by the modelling. Furthermore, a new system mode is introduced which is related to the new degree of freedom. The controller shows a high excitation of the new system mode for specific parameter combinations. Frequency-dependent feedbacks into the aerodynamics are also identified. Based on the comparison of both generator models, the analytical generator model promises a good trade-off between accuracy and computation time. In a second step, the effects of the identified interactions on turbine loads inside and outside the drive-train are analysed at the main bearing, the tower top, the tower base and the blade root. For this purpose, the equivalent loads of both models are compared. The load comparison shows that components inside and outside the drive-train are affected by the modelling. In particular, the main bearings and the tower show significant changes in load. However, loads can be increased as well as decreased compared to the state-of-the-art model. This supports the hypothesis of this work that a system design optimisation will differ from the component optimisation result. Furthermore, it can be shown that the added radial degrees of freedom and the electromagnetic forces add up in some cases and cancel each other out in other cases for load level changes. Based on the results of this work, follow-up questions arise, including lifetime estimation. Overall, this work contributes to a better understanding of the electro-mechanical interactions in direct-drive wind turbines and provides insight into the modelling approaches required for their analysis. It thus promotes the way towards system-oriented design of wind turbines.
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Simulation and evaluation of the hydroelastic responses of a tidal current turbine
(2017) Arnold, Matthias; Cheng, Po Wen (Prof. Dr.)
Tidal current energy offers the unique possibility of reliable and long-term predictable renewable energy. In contrast to the stochastic availability of wind and solar energy, the tides are predetermined by the planetary motions and are therefore a reliable energy source. This energy can be harvested with tidal current turbines. Compared to wind turbines, despite the same technological approach being used, the tidal current turbine differs strongly from a wind turbine in its geometries and conceptual approaches. Regardless, many assumptions for the design of the systems are transferred between the technologies. The present thesis challenges on of those assumptions, which states that the fluid-structure-interaction is dominated by the rotor blades and the tower, and evaluates the influence of different components like the nacelle or the main-shaft on the turbine's hydroelastic response. This is carried out with coupled CFD and Multibody simulations of the Voith HyTide1000-13 tidal current turbine.