scholarly journals Application of Asymptotic and Rigorous Techniques for the Characterization of Interferences Caused by a Wind Turbine in Its Neighborhood

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Maria Jesús Algar ◽  
Lorena Lozano ◽  
Javier Moreno ◽  
Iván González ◽  
Felipe Cátedra
Keyword(s):  
Wind Turbine ◽  
Method Of Moments ◽  
Scattered Field ◽  
High Frequency ◽  
Wind Farms ◽  
Uniform Theory Of Diffraction ◽  
Spline Surfaces ◽  
Radio Systems ◽  
Geometrical Theory Of Diffraction

This paper presents a complete assessment to the interferences caused in the nearby radio systems by wind turbines. Three different parameters have been considered: the scattered field of a wind turbine, its radar cross-section (RCS), and the Doppler shift generated by the rotating movements of the blades. These predictions are very useful for the study of the influence of wind farms in radio systems. To achieve this, both high-frequency techniques, such as Geometrical Theory of Diffraction/Uniform Theory of Diffraction (GTD/UTD) and Physical Optics (PO), and rigorous techniques, like Method of Moments (MoM), have been used. In the analysis of the scattered field, conductor and dielectric models of the wind turbine have been analyzed. In this way, realistic results can be obtained. For all cases under analysis, the wind turbine has been modeled with NURBS (Non-Uniform Rational B-Spline) surfaces since they allow the real shape of the object to be accurately replicated with very little information.

Aerodynamic Noise Characterization of a Full-Scale Wind Turbine through High-Frequency Surface Pressure Measurements

2015 ◽  
Vol 14 (5-6) ◽  
pp. 729-766 ◽  
Author(s):  
Franck Bertagnolio ◽  
Helge Aa. Madsen ◽  
Christian Bak ◽  
Niels Troldborg ◽  
Andreas Fischer
Keyword(s):  
Wind Turbine ◽  
Surface Pressure ◽  
High Frequency ◽  
Full Scale ◽  
Aerodynamic Noise ◽  
Pressure Measurements ◽  
Noise Characterization

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

MODELING OF HIGH FREQUENCY AMPLIFIERS FOR MODERN RADIO SYSTEMS

2019 ◽  
Author(s):  
Sergey Chumarov
Keyword(s):  
High Frequency ◽  
Radio Systems

The modeling features of high-frequency amplifiers are considered. The urgency of the development of such amplifiers is justified and the application areas are indicated. The stages of design of amplifiers are described in detail.

Characterization of Ni/γ-Al2O3 Catalyst Prepared by Atmospheric High Frequency Cold Plasma Jet for CO2 Reforming of CH4

2010 ◽  
Vol 31 (3) ◽  
pp. 353-359
Author(s):  
Xiaoyan CHAI ◽  
Shuyong SHANG ◽  
Gaihuan LIU ◽  
Xumei TAO ◽  
Xiang LI ◽  
...  
Keyword(s):  
High Frequency ◽  
Cold Plasma ◽  
Plasma Jet

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

scholarly journals Unsupervised Damage Detection for Offshore Jacket Wind Turbine Foundations Based on an Autoencoder Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3333
Author(s):  
Maria del Cisne Feijóo ◽  
Yovana Zambrano ◽  
Yolanda Vidal ◽  
Christian Tutivén
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Environmental Conditions ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Small Subset ◽  
Scaled Model ◽  
Vibration Data ◽  
Large Water

Structural health monitoring for offshore wind turbine foundations is paramount to the further development of offshore fixed wind farms. At present time there are a limited number of foundation designs, the jacket type being the preferred one in large water depths. In this work, a jacket-type foundation damage diagnosis strategy is stated. Normally, most or all the available data are of regular operation, thus methods that focus on the data leading to failures end up using only a small subset of the available data. Furthermore, when there is no historical precedent of a type of fault, those methods cannot be used. In addition, offshore wind turbines work under a wide variety of environmental conditions and regions of operation involving unknown input excitation given by the wind and waves. Taking into account the aforementioned difficulties, the stated strategy in this work is based on an autoencoder neural network model and its contribution is two-fold: (i) the proposed strategy is based only on healthy data, and (ii) it works under different operating and environmental conditions based only on the output vibration data gathered by accelerometer sensors. The proposed strategy has been tested through experimental laboratory tests on a scaled model.

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