scholarly journals A Fault Detection System for The Yaw Control of A HAWT Based on Neural Networking

2021 ◽  
Vol 85 (1) ◽  
pp. 135-142
Author(s):  
Ahmed R. El-Mallawany ◽  
Sameh Shaaban ◽  
Aida Abdel Hafiz
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Detection System ◽  
Operating Conditions ◽  
Horizontal Axis Wind Turbine ◽  
Yaw Control ◽  
Detection Approach ◽  
Simulation Results ◽  
Early Fault Detection ◽  
The Time Domain

The objective of the yaw control system in a horizontal axis wind turbine (HAWT) is to follow the wind direction with a minimum error. In this paper, a data driven fault detection approach of a HAWT is applied. Three simulation programs were utilized in order to model a 1.5 MW HAWT. These programs are Fatigue, Aerodynamics, Structures, and Turbulence(FAST), TurbSim, and MATLAB. The approach is implemented under normal operating scenarios while considering different wind velocities. Different kinds of faults were applied to the system for a nacelle-yaw angle error ranging from -10° to +20°. The simulation results of the Tower Top Deflection (TTD) in the time domain were transferred into frequency domain by Fast Fourier Transform (FFT). The output variables were used in order to build a Neural Networking, which will monitor the performance of the wind turbine. The built Neural Networking will also provide an early fault detection to avoid the operating conditions that lead to sudden turbine breakdown. The present work provides initial results that are useful for remote condition monitoring and assessment of a 1.5MW HAWT. The simulation results indicate that the implemented Neural Networking can achieve improvement of the wind turbine operation and maintenance level.

SCADA data as a powerful tool for early fault detection in wind turbine gearboxes

2020 ◽  
pp. 0309524X2096941
Author(s):  
Khaled Taha Abd-Elwahab ◽  
Ali Ahmed Hassan
Keyword(s):  
Wind Speed ◽  
Fault Detection ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Comparison Method ◽  
Operating Conditions ◽  
Tree Model ◽  
Aggregated Model ◽  
Early Fault Detection ◽  
Abnormal Performance

The different operating conditions of wind turbines pose great challenges for efficient and reliable fault detection. Therefore, a good analysis of wind turbine data is essential in assessing the state of the wind turbines, since the traditional threshold cannot provide a timely warning as it indicates that the malfunction has already occurred. This paper presents a new method for analyzing the actual data of the turbines, using aggregated model consisting of the neighborhood comparison method, K-means clustering and decision tree model to diagnose faults. The wind speed of the adjacent turbines is compared with each other, then other parameters of the same wind speed are also compared with each other. The purpose of comparison is that, the wind turbines which are similar in wind speed are similar in performance as well. This approach helps us to discover the abnormal data for turbine performance with in the normal operating range. The abnormal performance of any turbine destroys the similarity relationship between its data and the neighboring unit’s data. The main advantage of this approach is the possibility to detect the beginning of abnormal performance in real time, a case study using real SCADA data is used to validate this approach, which demonstrates its effectiveness and advantages.

Comparison of Wind Tunnel Airfoil Performance Data With Wind Turbine Blade Data

1992 ◽  
Vol 114 (2) ◽  
pp. 119-124 ◽  
Author(s):  
C. P. Butterfield ◽  
George Scott ◽  
Walt Musial
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Peak Power ◽  
Unsteady Aerodynamics ◽  
Leading Edge ◽  
Operating Conditions ◽  
Performance Data ◽  
Horizontal Axis Wind Turbine ◽  
Force Coefficients ◽  
Basic Fluid

Horizontal axis wind turbine (HAWT) performance is usually predicted by using wind tunnel airfoil performance data in a blade element momentum theory analysis. This analysis assumes that the rotating blade airfoils will perform as they do in the wind tunnel. However, when stall-regulated HAWT performance is measured in full-scale operation, it is common to find that peak power levels are significantly greater than those predicted. Pitch-controlled rotors experience predictable peak power levels because they do not rely on stall to regulate peak power. This has led to empirical corrections to the stall predictions. Viterna and Corrigan (1981) proposed the most popular version of this correction. But very little insight has been gained into the basic cause of this discrepancy. The National Renewable Energy Laboratory (NREL), funded by the DOE, has conducted the first phase of an experiment which is focused on understanding the basic fluid mechanics of HAWT aerodynamics. Results to date have shown that unsteady aerodynamics exist during all operating conditions and dynamic stall can exist for high yaw angle operation. Stall hysteresis occurs for even small yaw angles and delayed stall is a very persistent reality in all operating conditions. Delayed stall is indicated by a leading edge suction peak which remains attached through angles of attack (AOA) up to 30 degrees. Wind tunnel results show this peak separating from the leading edge at 18 deg AOA. The effect of this anomaly is to raise normal force coefficients and tangent force coefficients for high AOA. Increased tangent forces will directly affect HAWT performance in high wind speed operation. This report describes pressure distribution data resulting from both wind tunnel and HAWT tests. A method of bins is used to average the HAWT data which is compared to the wind tunnel data. The analysis technique and the test set-up for each test are described.

scholarly journals Numerical simulation of icing effect on aerodynamic characteristics of a wind turbine blade

2021 ◽  
Vol 25 (6 Part B) ◽  
pp. 4643-4650
Author(s):  
Yan Li ◽  
Lei Shi ◽  
Wen-Feng Guo ◽  
Kotaro Tagawa ◽  
Bin Zhao
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Aerodynamic Characteristics ◽  
Wind Turbine Blade ◽  
Horizontal Axis Wind Turbine ◽  
Ambient Temperatures ◽  
Research Findings ◽  
Simulation Results ◽  
Lift And Drag ◽  
Lift And Drag Coefficient

Icing accretion on wind turbine will degrade its performance, resulting in reduction of output power and even leading to accidents. For solving this problem, it is necessary to predict the icing type and shape on wind turbine blade, and evaluate the variation of aerodynamic characteristics. In this paper the icing types and shapes in presence of airfoil, selected from blade of 1.5 MW horizontal-axis wind turbine, are simulated under different ambient temperatures and icing time lengths. Based on the icing simulation results, the aerodynamic characteristics of icing airfoils are simulated, including lift and drag coefficient, lift-drag ratio, etc. The simulation results show that the glaze ice with two horns presents on airfoil under high ambient temperature such as -5?C. When ambient temperatures are low, such as -10?C and -15?C, the rime ices with streamline profiles present on the airfoil. With increase in icing time the lift forces and coefficients decrease, and the drag ones increase. According to the variations of lift-drag ratios of icing airfoil, the aerodynamic performance of airfoil deteriorates in the presence of icing. The glaze ice has great effect on aerodynamic characteristics of airfoil. The research findings lay theoretical foundation for icing wind tunnel experiment.

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.

Navier-Stokes and Comprehensive Analysis Performance Predictions of the NREL Phase VI Experiment

2003 ◽  
Author(s):  
Earl P. N. Duque ◽  
Michael D. Burklund ◽  
Wayne Johnson
Keyword(s):  
Experimental Data ◽  
Wind Turbine ◽  
Turbine Rotor ◽  
Operating Conditions ◽  
Navier Stokes ◽  
Horizontal Axis Wind Turbine ◽  
Performance Predictions ◽  
Nasa Ames Research ◽  
Nrel Phase Vi ◽  
Wind Turbine Rotor

A vortex lattice code, CAMRAD II, and a Reynolds-Averaged Navier-Stoke code, OVERFLOW-D2, were used to predict the aerodynamic performance of a two-bladed horizontal axis wind turbine. All computations were compared with experimental data that was collected at the NASA Ames Research Center 80-by 120-Foot Wind Tunnel. Computations were performed for both axial as well as yawed operating conditions. Various stall delay models and dynamics stall models were used by the CAMRAD II code. Comparisons between the experimental data and computed aerodynamic loads show that the OVERFLOW-D2 code can accurately predict the power and spanwise loading of a wind turbine rotor.

Adaptive fault detection of the bearing in wind turbine generators using parameterless empirical wavelet transform and margin factor

2019 ◽  
Vol 25 (6) ◽  
pp. 1263-1278 ◽  
Author(s):  
Wei Teng ◽  
Wei Wang ◽  
Haixing Ma ◽  
Yibing Liu ◽  
Zhiyong Ma ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Wind Turbines ◽  
Vibration Signal ◽  
Scale Space ◽  
Operating Conditions ◽  
Turbine Generators ◽  
Detection Approach ◽  
Empirical Wavelet Transform ◽  
Fault Information

Wind turbines revolve in difficult operating conditions due to stochastic loads and produce massive vibration signals, which cause obstacles in detecting potential fault information. To overcome this, an adaptive fault detection approach is presented in this paper on the basis of parameterless empirical wavelet transform (PEWT) and the margin factor. PEWT can decompose the vibration signal into a series of empirical modes (EMs) through splitting its Fourier spectrum, using the scale space method and adaptively constructing an orthogonal wavelet filter bank. The margin factor is utilized as a key metric for automatically selecting the EM which is sensitive to the potential faults. The method presented in this paper will improve the efficiency and accuracy of fault information for the condition monitoring of wind turbines.

scholarly journals Efficient contribution of partially tip cascaded horizontal-axis wind turbine

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989211
Author(s):  
Deyaa Nabil Elshebiny ◽  
Ali AbdelFattah Hashem ◽  
Farouk Mohammed Owis
Keyword(s):  
Wind Turbine ◽  
Aerodynamic Performance ◽  
Operating Conditions ◽  
Horizontal Axis ◽  
National Renewable Energy Laboratory ◽  
Horizontal Axis Wind Turbine ◽  
Ansys Fluent ◽  
Knowing That ◽  
Turbine Performance ◽  
Blade Tip

This article introduces novel blade tip geometric modification to improve the aerodynamic performance of horizontal-axis wind turbine by adding auxiliary cascading blades toward the tip region. This study focuses on the new turbine shape and how it enhances the turbine performance in comparison with the classical turbine. This study is performed numerically for National Renewable Energy Laboratory Phase II (non-optimized wind turbine) taking into consideration the effect of adding different cascade configurations on the turbine performance using ANSYS FLUENT program. The analysis of single-auxiliary and double-auxiliary cascade blades has shown an impact on increasing the turbine power of 28% and 76%, respectively, at 72 r/min and 12.85 m/s of wind speed. Knowing that the performance of cascaded wind turbine depends on the geometry, solidity and operating conditions of the original blade; therefore, these results are not authorized for other cases.

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