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Sökning: WFRF:(Ivanell Stefan Associate professor)

  • Resultat 1-6 av 6
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1.
  • Eriksson, Ola, 1979- (författare)
  • Numerical Computations of Wakes Behind Wind Farms : A tool to study Farm to Farm interaction
  • 2019
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • More and larger wind farms are planned offshore. As the most suitable sites to build are limited these new wind farms will be constructed near to each other in so called wind farm clusters. Behind the wind turbines in these farms there is a disrupted flow of air called a wake that is characterized by reduced wind speed and increased turbulence. These individual turbine wakes combine to form a farm wake that can travel long distances. In wind farm clusters farm to farm interaction will occur, i.e. the long distance wake from one wind farm will impact the wind conditions for other farms in the surrounding area.This thesis contains numerical studies of these long distance wakes. In these studies Large Eddy Simulations (LES) using an Actuator Disc method (ACD) are used. A prescribed boundary layer is used where the wind shear is introduced using body forces. The turbulence, based on the Mann model, is introduced as fluctuating body forces upstream of the farm. A neutral atmosphere is assumed. The applied method has earlier been used for studies of wake effects inside farms but not for the longer distances needed for the study of farm to farm interaction. Parameter studies are setup to analyze how to best use the model for the study of long distance wakes with regards to 1) numerical and physical parameters in the model, 2) the extension of the domain and turbulence as well as the characteristics of the flow far downstream and 3) the downstream development of turbulence with different combinations of wind shear and turbulence level.Using an initial simulation setup a wind farm was studied and preliminary results were obtained. These results were subsequently improved upon by applying the simulation setup adjustments indicated in the parameter studies. A comparison with a mesoscale model was also done. The mesoscale model was shown to be relevant for studies of long distance wakes in another study comparing LES and WRF. Finally an idealized farm to farm interaction case was studied with focus on the impact of including the Coriolis force in the simulations.Combining LES with a mesoscale model is of interest to study further.
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2.
  • Li, Zhongtian (författare)
  • Dynamic Thermal Rating for Improved Utilization of Wind Farm Export Systems : A Methodology for Improving Load Profile Estimation of Wind Farm Export Transformers
  • 2023
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The power system components connected to renewable energy sources, such as transformers, are often oversized and conservatively loaded. The design of transformers normally ignores the intermittent nature of the connected renewable energy sources (e.g. solar, wind). Due to the variations in weather conditions and operation states, the transformer load oscillates and the actual hot spot temperature is significantly lower than the designed thermal rating.For wind farms, the oversized transformer causes extra resourcematerial waste and a higher wind power price. Dynamic thermal rating can be applied to determine the rating of the transformers based on real-time environmental conditions (e.g. ambient temperature, wind speed). However, in order to optimize the operation of the transformers with dynamic thermal rating, the prediction of the load profile of transformers is an obstacle.The load of wind farm export transformers oscillates due to thechange of load conditions (e.g. turbine availability, power curtailment) and environmental conditions (e.g. wind speed, wind direction and ambient temperature). This thesis proposes a new methodology to improve the utilization of wind farm export transformers by estimating their load profile more accurately and assessing their aging rate. The estimation of the load profile takes the wake effect and turbine availability into account. Specifically, the variation in the wind turbine failure and repair rates, which is influenced by the wind, is considered in the evaluation of turbine availability. Additionally, a correction method is proposed to improve the accuracy of the wake loss computation.The results demonstrate that the estimation accuracy of the transformer load profile is improved after considering the influence of the wake effect and turbine availability. The wake effect and the turbine availability reduce the generated wind power and to some extent, reduce the load and the aging rate of transformers. However, the wake effect has limited influence when the wind farm reaches peak power production while turbine availability influences the load profile of transformers especially when the load is close to the installed capacity of the wind farm. After considering these two factors, the prediction accuracy of the hot spot temperature in the transformers can be enhanced and dynamic thermal rating can be applied to transformers with improved reliability.
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3.
  • Asmuth, Henrik (författare)
  • Efficient Large-­eddy Simulation for Wind Energy Applications
  • 2022
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Modelling the interaction of wind turbines with the ambient flow is essential for almost all technical aspects of wind energy exploitation. Large-eddy simulation (LES) is the most detailed approach feasible to model this complex interaction of wind turbines with the atmospheric boundary layer and the wakes of upstream turbines. Despite more than twenty years of fundamental research on wind turbine modelling with LES, applications of the method remain limited to academic use cases to date. The main bottleneck hindering a broader adoption of LES in the industrial practice is the large computational demand of the method. Nevertheless, it holds enormous potential for addressing various modelling challenges arising from current trends in wind energy.A promising alternative to classical numerical approaches for LES is the lattice Boltzmann method (LBM). In particular, GPU-based (graphics processing unit) implementations of the method provide significant performance gains and have enabled unprecedented computational efficiencies for LES in different fields of fluid dynamics. Still, the LBM´s potential for wind energy applications remains untapped due to open questions, some of which are specific to the field. This thesis addresses two specific problems in applications of LES to wind turbine and farm simulations. First, is the representation of wind turbines with the actuator line technique. And, second, is the modelling of the surface shear stress in simulations of atmospheric boundary layers. Both aspects are crucial to enable LES for wind energy applications with the LBM, as is usually done with conventional approaches.As for the former, an LBM implementation of the actuator line model is applied in multiple studies on wind turbine wakes. Code-to-code comparisons and experimental validations show that the model can accurately capture the aerodynamic forces acting on the turbine blades as well as the wake characteristics. For the simulation of boundary layer flows a novel LBM-specific wall model is developed. The model, referred to as inverse momentum exchange method, imposes the surface shear stress at the first offwall grid points by adjusting the slip velocity in bounce-back boundary schemes. Simulations are compared to theoretical, numerical, and experimental reference data of isothermal boundary layer flows. It is consistently found that both mean quantities and higherorder turbulence statistics can be well-captured by wall-modelled lattice Boltzmann LES using the presented wall model and the employed cumulant collision scheme.The results presented illustrate that the LBM is a suitable approach for state-of-the-art LES of wind turbine wakes and boundary layer flows. Moreover, the applied method is shown to be robust, and, above all, extremely computationally efficient. Based on the observed computational efficiencies, it is concluded that industry LES for wind energy applications is possible with GPU-based LBM solvers. Furthermore, additional studies presented in this thesis illustrate further potentials of the method. Such are applications of reinforcement learning to wind farm control or large-scale data generation for the training of deep learning models for wake predictions.
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4.
  • Barney, Andrew (författare)
  • Integrated regional energy planning for islands : Development of a decision-aiding methodological framework and application
  • 2022
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Clear and inclusive planning guidance for island planners seeking transitions away from traditional fossil fuel based energy systems is currently needed. At present, the guidance from the scientific community has largely been provided piecemeal and with significant focus on the specifics of single islands and, more often than not, on proposed energy systems’ techno-economics. To address these gaps in applicability and encourage a more balanced energy project analysis the REACT-DECARB integrated energy planning and decision-aiding platform has been developed. REACT-DECARB seeks to work as a comprehensive planning platform for island energy transition and this thesis investigates the ability of the platform to provide the support to planners needed to facilitate their transition planning. To do so the core concepts, descriptions and applications of decision making as well as a number of energy planning tools are presented. The platform is then described and its individual steps are applied to eight geographic islands within the EU. These applications of the platform identified key opportunities for the islands, such as significant RES potential, while also finding potential obstacles, such as land use conflicts. Further, it highlighted the high economic cost of seeking full electricity autonomy and of using substantial battery capacities. The platform additionally identified the importance local preferences can potentially have on the ranking of future energy scenarios as well as the impact lifetime project environmental costs can have on overall system environmental impacts. In summation, the REACT-DECARB platform is found to be an effective tool in directing island energy decarbonisation efforts by guiding local energy planners in what should be included in their planning and how these key elements can be incorporated in the decisions made. Further, the platform is found to be flexible enough to be applied to more than the specific circumstances of a single island and allows planners to adjust their approaches to its different steps as needed and to better match their capabilities.
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5.
  • Korb, Henry, 1996- (författare)
  • The Lattice Boltzmann Method for Wind Farm Simulations: Validation and Application
  • 2023
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Many new challenges in wind energy require the use of large eddy simulation for accurate modeling of wind farm flows. However, the immense computational cost hinders its use in research and industry. The lattice Boltzmann method is the most promising candidate to date to achieve the highest level of accuracy while decreasing computational cost by orders of magnitude compared to traditional methods. In this thesis, I present further development of the lattice Boltzmann method for wind energy and compile various applications, such as industrial use, generation of training data for machine learning, and analysis of wind farm control paradigms. In order to evaluate the requirements of different industrial stakeholders, we conduct a survey among industry experts on the use of large eddy simulation and show that the run time requirements indicated by many respondents can be met with the current state of the lattice Boltzmann method. In a validation study, the lattice Boltzmann method is as accurate as traditional Navier-Stokes solvers, while reducing computational cost by one to more orders of magnitude. A convolutional neural network is trained to predict average flow velocities in the wake of a single turbine. The predictions exhibit very high accuracy at execution times similar to engineering models. The lattice Boltzmann method enables the generation of larger training sets at a feasible computational cost. A proof of concept is provided for the use of reinforcement learning to discover new, cooperative wind farm control mechanisms. In an extensive analysis of the helix approach, its physical mechanisms are elucidated and a thorough parameter study of the wake of a single turbine is provided. We also study the interaction of multiple helical wakes, providing a way to extend the approach from a pair of turbines to wind farms.
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6.
  • Simisiroglou, Nikolaos (författare)
  • Wind power wake modelling : Development and application of an actuator disc method for industrial utilization.
  • 2018
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • As a wind turbine extracts energy from the wind it creates a region downstream where the wind velocity is decreased and the urbulence intensity is increased, this region is commonly called the wake region. Today’s wind farms include a large number of wind turbines position in tight layouts. These tight layouts result in increased power losses due to wakes, rendering accurate wind turbine wake modelling crucial in developing cost effective projects.The primary aim of this study is to create a method capable of conducting full-scale wind farm wake computations accurately in a time efficient manner by taking into account the computational resources and data availability of a typical industrial user. As a first step of this study, an actuator disc (ACD) method (old ACD) used within WindSim, is evaluated against power production data from the Lillgrund offshore wind. This study is followed by the development of a new ACD method. The new ACD method differs from the previous ACD method in terms of how the thrust distribution and the power production is calculated. A series of validation studies are performed on this newly introduced ACD method. These consist of validating the method against two cases with known analytical solutions, the research code EllipSys3D which uses Large Eddy Simulation (LES) based computations with an ACD approach and three differentwind tunnel set–ups. Lastly, a comparative analysis of the two ACD methods (old and new) and two analytical wake models is done using wind turbine power production data from Lillgrund.Results from the validation studies show that this new ACD method is able to predict the overall behaviour of the flow with low computational effort while also taking into account the availability of data for a typical industrial user. One may say that the new ACD method in RANS, which has much lower computational requirements than the ACD method in LES at the cost of lower accuracy, represents a good compromise. Lastly, the results from the new ACD method show a clear improvement in the estimated power production for the Lillgrund wind farm in comparison to the old ACD method.
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  • Resultat 1-6 av 6

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