Extreme learning approach with wavelet transform function for forecasting wind turbine wake effect to improve wind farm efficiency

2016 ◽  
Vol 96 ◽  
pp. 91-95 ◽  
Author(s):  
Igor Mladenović ◽  
Dušan Marković ◽  
Miloš Milovančević ◽  
Miroljub Nikolić
Keyword(s):  
Wavelet Transform ◽  
Wind Turbine ◽  
Wind Farm ◽  
Learning Approach ◽  
Wake Effect ◽  
Farm Efficiency ◽  
Turbine Wake ◽  
Wind Turbine Wake

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 Retraction Note to: Adapting project management method and ANFIS strategy for variables selection and analyzing wind turbine wake effect

2020 ◽  
Vol 103 (3) ◽  
pp. 3863-3863
Author(s):  
Dalibor Petković ◽  
Siti Hafizah Ab Hamid ◽  
Žarko Ćojbašić ◽  
Nenad T. Pavlović
Keyword(s):  
Project Management ◽  
Wind Turbine ◽  
Wake Effect ◽  
Variables Selection ◽  
Management Method ◽  
Turbine Wake ◽  
Wind Turbine Wake

scholarly journals Analysis of rotorcraft wind turbine wake encounters using piloted simulation

2021 ◽  
Author(s):  
Alexander Štrbac ◽  
Tanja Martini ◽  
Daniel H. Greiwe ◽  
Frauke Hoffmann ◽  
Michael Jones
Keyword(s):  
Wind Turbine ◽  
Alternative Energy ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Vortex Wake ◽  
Offshore Wind Farms ◽  
Turbine Wake ◽  
Wind Turbine Wake

AbstractThe use of offshore wind farms in Europe to provide a sustainable alternative energy source is now considered normal. Particularly in the North Sea, a large number of wind farms exist with a significant distance from the coast. This is becoming standard practice as larger areas are required to support operations. Efficient transport and monitoring of these wind farms can only be conducted using helicopters. As wind turbines continue to grow in size, there is a need to continuously update operational requirements for these helicopters, to ensure safe operations. This study assesses German regulations for flight corridors within offshore wind farms. A semi-empirical wind turbine wake model is used to generate velocity data for the research flight simulator AVES. The reference offshore wind turbine NREL 5 MW has been used and scaled to represent wind turbine of different sizes. This paper reports result from a simulation study concerning vortex wake encounter during offshore operations. The results have been obtained through piloted simulation for a transport case through a wind farm. Both subjective and objective measures are used to assess the severity of vortex wake encounters.

RETRACTED: Estimation of wind turbine wake effect by adaptive neuro-fuzzy approach

2015 ◽  
Vol 45 ◽  
pp. 1-6 ◽  
Author(s):  
Eiman Tamah Al-Shammari ◽  
Mohsen Amirmojahedi ◽  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
Nenad T. Pavlović ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Fuzzy Approach ◽  
Wake Effect ◽  
Neuro Fuzzy ◽  
Turbine Wake ◽  
Wind Turbine Wake

scholarly journals Distinct Turbulent Regions in the Wake of a Wind Turbine and Their Inflow-Dependent Locations: The Creation of a Wake Map

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5392
Author(s):  
Ingrid Neunaber ◽  
Michael Hölling ◽  
Richard J. A. M. Stevens ◽  
Gerard Schepers ◽  
Joachim Peinke
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Isotropic Turbulence ◽  
Turbulence Modeling ◽  
Wind Farms ◽  
Reference Case ◽  
Mean Velocity ◽  
Turbulence Analysis ◽  
Turbine Wake ◽  
Wind Turbine Wake

Wind turbines are usually clustered in wind farms which causes the downstream turbines to operate in the turbulent wakes of upstream turbines. As turbulence is directly related to increased fatigue loads, knowledge of the turbulence in the wake and its evolution are important. Therefore, the main objective of this study is a comprehensive exploration of the turbulence evolution in the wind turbine’s wake to identify characteristic turbulence regions. For this, we present an experimental study of three model wind turbine wake scenarios that were scanned with hot-wire anemometry with a very high downstream resolution. The model wind turbine was exposed to three inflows: laminar inflow as a reference case, a central wind turbine wake, and half of the wake of an upstream turbine. A detailed turbulence analysis reveals four downstream turbulence regions by means of the mean velocity, variance, turbulence intensity, energy spectra, integral and Taylor length scales, and the Castaing parameter that indicates the intermittency, or gustiness, of turbulence. In addition, a wake core with features of homogeneous isotropic turbulence and a ring of high intermittency surrounding the wake can be identified. The results are important for turbulence modeling in wakes and optimization of wind farm wake control.

scholarly journals Investigation of modified AD/RANS models for wind turbine wake predictions in large wind farm

2014 ◽  
Vol 524 ◽  
pp. 012151 ◽  
Author(s):  
L L Tian ◽  
W J Zhu ◽  
W Z Shen ◽  
J N Sørensen ◽  
N Zhao
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Rans Models ◽  
Turbine Wake ◽  
Large Wind ◽  
Wind Turbine Wake

Wind turbine wakes over hills

2018 ◽  
Vol 855 ◽  
pp. 671-702 ◽  
Author(s):  
Sina Shamsoddin ◽  
Fernando Porté-Agel
Keyword(s):  
Pressure Gradient ◽  
Wind Turbine ◽  
Wind Farm ◽  
Internal Boundary ◽  
Windward Side ◽  
Leeward Side ◽  
Horizontal Line ◽  
The Hill ◽  
Turbine Wake ◽  
Wind Turbine Wake

Understanding and predicting the behaviour of wind turbine wake flows over hills is important for optimal design of wind-farm configurations on topography. In this study, we present an analytical modelling framework together with large-eddy simulation (LES) results to investigate turbine wakes over two-dimensional hills. The analytical model consists of two steps. In the first step, we deal with the effect of the pressure gradient on the wake evolution; and in the second step, we consider the effect of the hill-induced streamline distortion on the wake. This model enables us to obtain the wake recovery rate, the mean velocity and velocity deficit profiles and the wake trajectory in the presence of the hill. Moreover, we perform LES to test our model and also to obtain new complementary insight about such flows. Especially, we take advantage of the LES data to perform a special analysis of the behaviour of the wake on the leeward side of the hill. It is found that the mainly favourable pressure gradient on the windward side of the hill accelerates the wake recovery and the adverse pressure gradient on the leeward side decelerates it. The wake trajectory for a hill of the same height as the turbine’s hub height is found to closely follow the hill profile on the windward side, but it maintains an almost constant elevation (a horizontal line) downstream of the hilltop. The trajectory of the wake on the leeward side is also studied for a limiting case of an escarpment, and it is shown that an internal boundary layer forms on the plateau which leads to an upward displacement of the wake centre. Finally, a parametric study of the position of the turbine with respect to the hill is performed to further elucidate the effect of the hill-induced pressure gradient on the wind turbine wake recovery.

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