scholarly journals Alignment of scanning lidars in offshore wind farms

2021 ◽  
Author(s):  
Andreas Rott ◽  
Jörge Schneemann ◽  
Frauke Theuer ◽  
Juan José Trujillo Quintero ◽  
Martin Kühn
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Farms ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Alignment Error ◽  
Position Information ◽  
Measurement Campaign ◽  
Scanning Lidar ◽  
Range Scanning

Abstract. Long-range Doppler wind lidars are applied more and more for high resolution areal measurements in and around wind farms. Proper alignment, or at least knowledge on how the systems are aligned, is of great relevance here. The paper describes in detail two methods that allow a very accurate alignment of a long-range scanning lidar without the use of extra equipment or sensors. The well-known so-called Hard Targeting allows a very precise positioning and north alignment of the lidar using the known positions of the surrounding obstacles, e.g. wind turbine towers. Considering multiple hard targets instead of only one with a given position in an optimization algorithm allows to increase the position information of the lidar device and minimizes the consequences of using erroneous input data. The method, referred to as Sea Surface Leveling, determines the leveling of the device during offshore campaigns in terms of roll and pitch angle based on distance measurements to the water surface. This is particularly well suited during the installation of the systems to minimize alignment error from the start, but it can also be used remotely during the measurement campaign for verification purposes. We applied and validated these methods to data of an offshore measurement campaign, where a commercial long-range scanning lidar was installed on the transition piece platform of a wind turbine. In addition, we present a model that estimates the quasi-static inclination of the device due to the thrust loading of the wind turbine at different operating conditions. The results show reliable outcomes with a very high accuracy in the range of 0.02° in determining the leveling. The importance of the exact alignment as well as the possible applications are discussed in this paper. In conclusion, these methods are useful tools that can be applied without extra effort and contribute significantly to the quality of successful measurement campaigns.

scholarly journals Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar

2014 ◽  
Vol 31 (7) ◽  
pp. 1529-1539 ◽  
Author(s):  
Matthew L. Aitken ◽  
Julie K. Lundquist
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Farm ◽  
Thrust Coefficient ◽  
Velocity Deficit ◽  
Scanning Lidar ◽  
Range Scanning ◽  
Utility Scale ◽  
Turbine Wake ◽  
Wind Turbine Wake

Abstract To facilitate the optimization of turbine spacing at modern wind farms, computational simulations of wake effects must be validated through comparison with full-scale field measurements of wakes from utility-scale turbines operating in the real atmosphere. Scanning remote sensors are particularly well suited for this objective, as they can sample wind fields over large areas at high temporal and spatial resolutions. Although ground-based systems are useful, the vantage point from the nacelle is favorable in that scans can more consistently transect the central part of the wake. To the best of the authors’ knowledge, the work described here represents the first analysis in the published literature of a utility-scale wind turbine wake using nacelle-based long-range scanning lidar. The results presented are of a field experiment conducted in the fall of 2011 at a wind farm in the western United States, quantifying wake attributes such as the velocity deficit, centerline location, and wake width. Notable findings include a high average velocity deficit, decreasing from 60% at a downwind distance x of 1.8 rotor diameters (D) to 40% at x = 6D, resulting from a low average wind speed and therefore a high average turbine thrust coefficient. Moreover, the wake width was measured to expand from 1.5D at x = 1.8D to 2.5D at x = 6D. Both the wake growth rate and the amplitude of wake meandering were observed to be greater for high ambient turbulence intensity and daytime conditions as compared to low turbulence and nocturnal conditions.

scholarly journals Offshore wind farm global blockage measured with scanning lidar

2021 ◽  
Vol 6 (2) ◽  
pp. 521-538
Author(s):  
Jörge Schneemann ◽  
Frauke Theuer ◽  
Andreas Rott ◽  
Martin Dörenkämper ◽  
Martin Kühn
Keyword(s):  
Wind Speed ◽  
Long Range ◽  
Wind Farm ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Stability Estimates ◽  
Offshore Wind Farm ◽  
Scanning Lidar ◽  
High Thrust ◽  
Blockage Effect

Abstract. The objective of this paper was the experimental investigation of the accumulated induction effect of a large offshore wind farm as a whole, i.e. the global-blockage effect, in relation to atmospheric-stability estimates and wind farm operational states. We measured the inflow of a 400 MW offshore wind farm in the German North Sea with a scanning long-range Doppler wind lidar. A methodology to reduce the statistical variability of different lidar scans at comparable measurement conditions was introduced, and an extensive uncertainty assessment of the averaged wind fields was performed to be able to identify the global-blockage effect, which is small compared to e.g. wind turbine wake effects and ambient variations in the inflow. Our results showed a 4 % decrease in wind speed (accuracy range of 2 % to 6 %) at transition piece height (24.6 m) upwind of the wind farm with the turbines operating at high thrust coefficients above 0.8 in a stably stratified atmosphere, which we interpreted as global blockage. In contrast, at unstable stratification and similar operating conditions and for situations with low thrust coefficients (i.e. approx. 0 for not operating turbines and ≤ 0.3 for turbines operating far above rated wind speed) we identified no wind speed deficit. We discussed the significance of our measurements and possible sources of error in long-range scanning lidar campaigns and give recommendations on how to measure small flow effects like global blockage with scanning Doppler lidar. In conclusion, we provide strong evidence for the existence of global blockage in large offshore wind farms in stable stratification and the turbines operating at a high thrust coefficient by planar lidar wind field measurements. We further conclude that global blockage is dependent on atmospheric stratification.

scholarly journals Offshore wind farm global blockage measured with scanning lidar

2020 ◽  
Author(s):  
Jörge Schneemann ◽  
Frauke Theuer ◽  
Andreas Rott ◽  
Martin Dörenkämper ◽  
Martin Kühn
Keyword(s):  
Wind Speed ◽  
Long Range ◽  
Wind Farm ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Stability Estimates ◽  
Offshore Wind Farm ◽  
Scanning Lidar ◽  
High Thrust ◽  
Blockage Effect

Abstract. The objective of this paper was the experimental investigation of the accumulated induction effect of a large offshore wind farm as a whole, i.e. the global blockage effect, in relation to atmospheric stability estimates and wind farm operational states. We measured the inflow of a 400 MW offshore wind farm in the German North Sea with a scanning long-range Doppler wind lidar. A methodology to reduce the statistical variability of different lidar scans at comparable measurement conditions was introduced and an extensive uncertainty assessment of the averaged wind fields was performed to be able to identify the global blockage effect which is small compared to e.g. wind turbine wake effects and ambient variations in the inflow. Our results showed a significant decrease in wind speed at platform height in front of the wind farm of 4.5 % within an accuracy range between 2.5 % and 6.5 % with the turbines operating at high thrust coefficients in a stably stratified atmosphere, which we interpreted as global blockage. In contrast, at unstable stratification and similar operating conditions we identified no wind speed deficit. We discussed the significance of our measurements, possible sources of error in long-range scanning lidar campaigns and give recommendations how to measure small flow effects like global blockage with scanning Doppler lidar. In conclusion, we provide strong evidence for the existence of global blockage in large offshore wind farms in stable stratification and the turbines operating at a high thrust coefficient by planar lidar wind field measurements. We conclude that global blockage is dependant on atmospheric stratification.

scholarly journals Low-Speed Bearing Fault Diagnosis Based on Permutation and Spectral Entropy Measures

2020 ◽  
Vol 10 (13) ◽  
pp. 4666
Author(s):  
Diego Sandoval ◽  
Urko Leturiondo ◽  
Francesc Pozo ◽  
Yolanda Vidal
Keyword(s):  
Damage Detection ◽  
Wind Turbine ◽  
Wind Farms ◽  
Vibration Signal ◽  
General Purpose ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Permutation Entropy ◽  
Offshore Wind Farms ◽  
Low Speed

Despite its influence on wind energy service life, condition-based maintenance is still challenging to perform. For offshore wind farms, which are placed in harsh and remote environments, damage detection is critically important to schedule maintenance tasks and reduce operation and maintenance costs. One critical component to be monitored on a wind turbine is the pitch bearing, which can operate at low speed and high loads. Classical methods and features for general purpose bearings cannot be applied effectively to wind turbine pitch bearings owing to their specific operating conditions (high loads and non-constant very low speed with changing direction). Thus, damage detection of wind turbine pitch bearings is currently a challenge. In this study, entropy indicators are proposed as an alternative to classical bearing analysis. For this purpose, spectral and permutation entropy are combined to analyze a raw vibration signal from a low-speed bearing in several scenarios. The results indicate that entropy values change according to different types of damage on bearings, and the sensitivity of the entropy types differs among them. The study offers some important insights into the use of entropy indicators for feature extraction and it lays the foundation for future bearing prognosis methods.

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.

scholarly journals Dynamic Modeling of an Offshore Floating Wind Turbine for Application in the Mediterranean Sea

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 248
Author(s):  
Lorenzo Cottura ◽  
Riccardo Caradonna ◽  
Alberto Ghigo ◽  
Riccardo Novo ◽  
Giovanni Bracco ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Mediterranean Sea ◽  
Wind Farm ◽  
Reference Model ◽  
Wide Spectrum ◽  
Wind Farms ◽  
Offshore Wind ◽  
Floating Wind Turbine ◽  
The Mediterranean ◽  
Offshore Floating Wind Turbine

Wind power is emerging as one of the most sustainable and low-cost options for energy production. Far-offshore floating wind turbines are attractive in view of exploiting high wind availability sites while minimizing environmental and landscape impact. In the last few years, some offshore floating wind farms were deployed in Northern Europe for technology validation, with very promising results. At present time, however, no offshore wind farm installations have been developed in the Mediterranean Sea. The aim of this work is to comprehensively model an offshore floating wind turbine and examine the behavior resulting from a wide spectrum of sea and wind states typical of the Mediterranean Sea. The flexible and accessible in-house model developed for this purpose is compared with the reference model FAST v8.16 for verifying its reliability. Then, a simulation campaign is carried out to estimate the wind turbine LCOE (Levelized Cost of Energy). Based on this, the best substructure is chosen and the convenience of the investment is evaluated.

Model Test and Numerical Analysis of an Offshore Bottom Fixed Pentapod Wind Turbine Under Seismic Loads

2016 ◽  
Author(s):  
Wenhua Wang ◽  
Zhen Gao ◽  
Xin Li ◽  
Torgeir Moan ◽  
Bin Wang
Keyword(s):  
Wind Turbine ◽  
Wind Wave ◽  
Seismic Analysis ◽  
Wind Farms ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Test Model ◽  
Structural Dynamic ◽  
Load Conditions

In the last decade the wind energy industry has developed rapidly in China, especially offshore. For a water depth less than 20m, monopile and multi-pile substructures (tripod, pentapod) are applied widely in offshore wind farms. Some wind farms in China are located in high seismicity regions, thus, the earthquake load may become the dominant load for offshore wind turbines. This paper deals with the seismic behavior of an offshore wind turbine (OWT) consisting of the NREL 5MW baseline wind turbine, a pentapod substructure and a pile foundation of a real offshore wind turbine in China. A test model of the OWT is designed based on the hydro-elastic similarity. Test cases of different load combinations are performed with the environmental conditions generated by the Joint Earthquake, Wave and Current Simulation System and the Simple Wind Field Generation System at Dalian University of Technology, China, in order to investigate the structural dynamic responses under different load conditions. In the tests, a circular disk is used to model the rotor-nacelle system, and a force gauge is fixed at the center of the disk to measure the wind forces during the tests. A series of accelerometers are arranged along the model tower and the pentapod piles, and strain gauges glued on the substructure members are intended to measure the structural dynamic responses. A finite element model of the complete wind turbine is also established in order to compare the theoretical results with the test data. The hydro-elastic similarity is validated based on the comparison of the measured dynamic characteristics and the results of the prototype modal analysis. The numerical results agree well with the experimental data. Based on the comparisons of the results, the effect of the wind and sea loads on the structural responses subjected to seismic is demonstrated, especially the influence on the global response of the structure. It is seen that the effect of the combined seismic, wind, wave and current load conditions can not be simply superimposed. Hence the interaction effect in the seismic analysis should be considered when the wind, wave and current loads have a non-negligible effect.

scholarly journals Modeling and simulation of forces applied to the horizontal axis wind turbine rotors by the vortex method coupled with the method of the blade element

2021 ◽  
Vol 12 (1) ◽  
pp. 413
Author(s):  
Ibtissem Barkat ◽  
Abdelouahab Benretem ◽  
Fawaz Massouh ◽  
Issam Meghlaoui ◽  
Ahlem Chebel
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farms ◽  
Vortex Method ◽  
Operating Conditions ◽  
Horizontal Axis ◽  
Rotor Blades ◽  
Good Representation ◽  
Horizontal Axis Wind Turbine ◽  
Blade Element

This article aims to study the forces applied to the rotors of horizontal axis wind turbines. The aerodynamics of a turbine are controlled by the flow around the rotor, or estimate of air charges on the rotor blades under various operating conditions and their relation to the structural dynamics of the rotor are critical for design. One of the major challenges in wind turbine aerodynamics is to predict the forces on the blade as various methods, including blade element moment theory (BEM), the approach that is naturally adapted to the simulation of the aerodynamics of wind turbines and the dynamic and models (CFD) that describes with fidelity the flow around the rotor. In our article we proposed a modeling method and a simulation of the forces applied to the horizontal axis wind rotors turbines using the application of the blade elements method to model the rotor and the vortex method of free wake modeling in order to develop a rotor model, which can be used to study wind farms. This model is intended to speed up the calculation, guaranteeing a good representation of the aerodynamic loads exerted by the wind.

Wind Energy Perspectives in Myanmar

2020 ◽  
pp. 181-210
Author(s):  
Evgenii Ignatev ◽  
Galina Deryugina ◽  
Htet Myat Htoon ◽  
Mikhail Tyagunov
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
West Coast ◽  
Wind Farms ◽  
Offshore Wind ◽  
Optimal Composition ◽  
Construction Sites ◽  
Offshore Wind Farms ◽  
Installed Capacity ◽  
Energy Shortage

One of Myanmar's problems is energy shortage. Partially, energy shortage can possibly be decreased by the construction of sizeable grid-connected offshore wind farms. Eight prospective construction sites were selected and wind turbine models chosen. This chapter describes the method for determining the optimal composition of the wind farms complex, consisting of several offshore wind farms located at a considerable distance from each other in areas with significant wind regime asynchrony. To illustrate this method, the optimal composition with an installed capacity of 47.6 MW and located off Myanmar's west coast is defined.

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