Optimized Constant-Life Diagram for the Analysis of Fiberglass Composites Used in Wind Turbine Blades

2005 ◽  
Vol 127 (4) ◽  
pp. 563-569 ◽  
Author(s):  
Herbert J. Sutherland ◽  
John F. Mandell
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Damage Model ◽  
Wind Farms ◽  
Materials Testing ◽  
Optimum Number ◽  
Wind Turbine Blades ◽  
Design Standards ◽  
Fiberglass Composite ◽  
Nonlinear Damage Model

Mandell et al. have recently presented an updated constant-life diagram (CLD) for a fiberglass composite that is a typical wind turbine blade material. Their formulation uses the MSU/DOE fatigue data base to develop a CLD with detailed S-N information at 13 R-values. This diagram is the most detailed to date, and it includes several loading conditions that have been poorly represented in earlier studies. Sutherland and Mandell have used this formulation to analyze typical loads data from operating wind farms and the failure of coupons subjected to spectral loading. The detailed CLD used in these analyses requires a significant investment in materials testing that is usually outside the bounds of typical design standards for wind turbine blades. Thus, the question has become: How many S-N curves are required for the construction of a CLD that is sufficient for an “accurate” prediction of equivalent fatigue loads and service lifetimes? To answer this question, the load data from two operating wind turbines and the failure of coupons tested using the WISPERX spectra are analyzed using a nonlinear damage model. For the analysis, the predicted service lifetimes that are based on the CLD constructed from 13 R-values are compared to the predictions for CLDs constructed with fewer R-values. The results illustrate the optimum number of R-values is 5 with them concentrated between R-values of −2 and 0.5, or −2 and 0.7.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

Machine Learning Aided Prediction of Rain Erosion Damage on Wind Turbine Blade Sections

2021 ◽  
Author(s):  
Alessio Castorrini ◽  
Paolo Venturini ◽  
Fabrizio Gerboni ◽  
Alessandro Corsini ◽  
Franco Rispoli
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Energy Production ◽  
Turbine Blades ◽  
Wind Farms ◽  
Wind Turbine Blade ◽  
Wind Turbine Blades ◽  
Coating Materials ◽  
Erosion Modelling ◽  
Rain Erosion

Abstract Rain erosion of wind turbine blades represents an interesting topic of study due to its non-negligible impact on annual energy production of the wind farms installed in rainy sites. A considerable amount of recent research works has been oriented to this subject, proposing rain erosion modelling, performance losses prediction, structural issues studies, etc. This work aims to present a new method to predict the damage on a wind turbine blade. The method is applied here to study the effect of different rain conditions and blade coating materials, on the damage produced by the rain over a representative section of a reference 5MW turbine blade operating in normal turbulence wind conditions.

scholarly journals WIND FARMS AND AVIATION

Aviation ◽  
2009 ◽  
Vol 13 (2) ◽  
pp. 56-59 ◽  
Author(s):  
Andrej Novák
Keyword(s):  
Wind Turbine ◽  
Slovak Republic ◽  
Turbine Blades ◽  
Wind Farms ◽  
Wind Turbine Blades ◽  
Physical Size ◽  
Aviation Operations

Wind is an increasingly important source of energy for the Slovak Republic. It is exploited by the use of turbines to generate electricity. Because of their physical size, in particular their height, wind farms can have an effect on aviation. Additionally, rotating wind turbine blades may have an impact on certain aviation operations, particularly those involving radar. Santrauka Vejas yra vis didejantis energijos šaltinis Slovakijos Respublikoje. Jis naudojamas generuoti elektra turbinomis. Vejo fermos pagal savo fizikini dydi ir ypač pagal aukšti gali tureti itakos aviacijai. Besisukančios vejo turbinu mentes gali tureti itakos tam tikroms aviacijos operacijoms, ypač susijusioms su radarais.

Development of wireless bird collision monitoring system using 0-3 piezoelectric composite sensor on wind turbine blades

2017 ◽  
Vol 29 (17) ◽  
pp. 3426-3435
Author(s):  
Sang-Hyeon Kang ◽  
Lae-Hyong Kang
Keyword(s):  
Wind Turbine ◽  
Monitoring System ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Wind Farms ◽  
Clean Energy ◽  
Piezoelectric Composite ◽  
Collision Rate ◽  
Wind Turbine Blades ◽  
The Impact

Over the past several decades, wind turbines have been established as one of the promising renewable energy systems for safe and clean energy collection. In order to collect more energy efficiently, the size of wind turbines has been increased and many wind farms have been constructed. Wind farms generate lots of energy, but they cause several side effects, such as noise and a threat to wildlife. It is reported that the bird collision rate of a wind turbine ranges from 0.01 to 23 annually. It is more serious in the case of rare and endangered birds. In order to monitor the effect on birds in wind farms, researchers have developed remote sensing technology for a detection apparatus using heat and radar. In addition, paint color and other variables have been studied regarding their effects on the collision rate. However, the existing methods are passive ways to prevent bird collision or just monitor bird conditions. Therefore, in this study, we propose a bird collision monitoring system that can detect where the bird collision occurred, which will aid in rescuing the birds. If the wind turbine blade has its own ability to capture an impact signal, the impact location can be easily detected, and the birds can be rescued. For this purpose, piezoelectric paint was applied to the wind turbine blades used in this study. The piezoelectric paint is also known as 0-3 piezoelectric composite, which is composed of piezoelectric particles and polymer resin. It is sensitive to high-frequency signals such as impacts, so it is suitable for monitoring bird collision signals. In order to amplify and transmit the impact signal from the rotating blade to a stationary base, a wireless transmission device using a ZigBee module and signal conditioning circuit was also installed. Through lab-scale tests, it was confirmed that this bird collision monitoring system shows a 100% bird collision detection rate.

Life prediction of wind turbine blades using multi-scale damage model

2021 ◽  
pp. 073168442199588
Author(s):  
Sepideh Aghajani ◽  
Mohammadreza Hemati ◽  
Shams Torabnia
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Fatigue Damage ◽  
Life Prediction ◽  
Turbine Blades ◽  
Damage Model ◽  
Fatigue Loading ◽  
Multiaxial Fatigue ◽  
Wind Turbine Blade ◽  
Wind Turbine Blades

Wind turbine blade life prediction is the most important parameter to estimate the power generation cost. Due to the price and importance of wind blade, many experimental and theoretical methods were developed to estimate damages and blade life. A novel multiaxial fatigue damage model is suggested for the life prediction of a wind turbine blade. Fatigue reduction of fiber and interfiber characteristics are separately treated and simulated in this research. Damage behavior is considered in lamina level and then extended to laminate; hence, this model can be used for multidirectional laminated composites. The procedure of fatigue-induced degradation is implemented in an ABAQUS user material subroutine. By applying the fatigue damage model, life is estimated by the satisfaction of lamina fracture criteria. This model provides a comprehensive idea about how damage happens in wind blades regarding a multi-axis fatigue loading condition.

scholarly journals WRF Modeling of Deep Convection and Hail for Wind Power Applications

2020 ◽  
Vol 59 (10) ◽  
pp. 1717-1733 ◽  
Author(s):  
F. Letson ◽  
T. J. Shepherd ◽  
R. J. Barthelmie ◽  
S. C. Pryor
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Power ◽  
Model Simulation ◽  
Deep Convection ◽  
Turbine Blades ◽  
Wind Farms ◽  
Wind Turbine Blades ◽  
Wind Speeds ◽  
The Impact

AbstractDeep convection and the related occurrence of hail, intense precipitation, and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading-edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the U.S. southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) Model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modeling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements, and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates, and precipitation totals show good agreement with observations. The occurrence of precipitation during power-producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modeled with a mean proportion correct of 0.77 and an odds ratio of 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry, and there is evidence for positive model bias in cloud reflectivity.

A modified composite fatigue damage model considering stiffness evolution for wind turbine blades

2020 ◽  
Vol 233 ◽  
pp. 111736 ◽  
Author(s):  
Hongwei Liu ◽  
Zhichun Zhang ◽  
Hongbo Jia ◽  
Yanju Liu ◽  
Jinsong Leng
Keyword(s):  
Wind Turbine ◽  
Fatigue Damage ◽  
Turbine Blades ◽  
Damage Model ◽  
Wind Turbine Blades

scholarly journals Effects of defects in composite wind turbine blades – Part 2: Progressive damage modeling of fiberglass-reinforced epoxy composites with manufacturing-induced waves

2017 ◽  
Vol 2 (2) ◽  
pp. 653-669 ◽  
Author(s):  
Jared W. Nelson ◽  
Trey W. Riddle ◽  
Douglas S. Cairns
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Damage Model ◽  
Peak Stress ◽  
Failure Criteria ◽  
Progressive Damage ◽  
Damage Modeling ◽  
Cohesive Elements ◽  
Wind Turbine Blades ◽  
Nonlinear Shear

Abstract. Composite wind turbine blades are typically reliable; however, premature failures are often in regions of manufacturing defects. While the use of damage modeling has increased with improved computational capabilities, they are often performed for worst-case scenarios in which damage or defects are replaced with notches or holes. To better understand and predict these effects, an effects-of-defects study has been undertaken. As a portion of this study, various progressive damage modeling approaches were investigated to determine if proven modeling capabilities could be adapted to predict damage progression of composite laminates with typical manufacturing flaws commonly found in wind turbine blades. Models were constructed to match the coupons from, and compare the results to, the characterization and material testing study presented as a companion. Modeling methods were chosen from established methodologies and included continuum damage models (linear elastic with Hashin failure criteria, user-defined failure criteria, nonlinear shear criteria), a discrete damage model (cohesive elements), and a combined damage model (nonlinear shear with cohesive elements). A systematic, combined qualitative–quantitative approach was used to compare consistency, accuracy, and predictive capability for each model to responses found experimentally. Results indicated that the Hashin and combined models were best able to predict material response to be within 10 % of the strain at peak stress and within 10 % of the peak stress. In both cases, the correlation was not as accurate as the wave shapes were changed in the model; correlation was still within 20 % in many cases. The other modeling approaches did not correlate well within the comparative framework. Overall, the results indicate that this combined approach may provide insight into blade performance with known defects when used in conjunction with a probabilistic flaw framework.

Far-Field Noise Prediction of Wind Turbines at Different Receivers and Wind Speeds: A Computational Study

2015 ◽  
Author(s):  
Fardin Khalili ◽  
Pradip Majumdar ◽  
Mehdi Zeyghami
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Wind Farms ◽  
Acoustic Power ◽  
Far Field ◽  
Wind Turbine Blades ◽  
Wind Speeds ◽  
Field Noise ◽  
Field Sound

Far-field noise propagation from wind turbines propel development of wind farms to an issue for public acceptance. Airstream contains pressure fluctuations as a result of instability, giving a regular eddy pattern or an irregular turbulent motion which are responsible for the sound produced by wind turbine blades. Aeroacoustic noise emanated from a wind turbine is mainly generated by the interactions of tip and trailing edge of wind turbine blades with the mechanics in wake region such as inflow turbulence structures, boundary layer separation and vortex shedding. Hence, there is a strong necessity for an analytical investigation for noise reducing design and development of the technology in order to further expand wind farms. The objectives of this study are to analyze the far-field aeroacoustics of wind turbines with the purpose of predicting far-field sound pressure levels at different receivers and monitoring total acoustic power captured within wind turbine performance for various wind speeds. Blades are modeled based on NREL S825 airfoil since it has high maximum lift and low profile drag. With the purpose of predicting far-field noise, the Ffowcs Williams-Hawkings (FW-H) acoustics model is the preferred method in order to compute the far-field sound signal which is released from near-field flow. As the key attribute of the research, detached eddy simulation (DES) provides accurate results for the desired simulation since it is a hybrid modeling approach that combines features of Reynolds-averaged Navier-Stokes (RANS) simulation in boundary layers and irrotational flow regions, and large-eddy simulation (LES) in unsteady separation regions. In addition, SST K-Omega detached eddy turbulence model is used due to its good compromise between robustness, computational cost and accuracy. Aerodynamic and aeroacoustic analysis of a wind turbine is performed using a three-dimensional model and a commercial CFD Software, STAR-CCM+. In order to predict far-field sound pressure levels and acoustic powers on different locations, five point receivers are defined downstream of the wind turbine model. Receivers are placed one diameter, D, over the wind turbine rotor blades with 1D, 2D, 5D, 10D and 15D away from the wind turbine that represent receivers 1 to 5. Higher acoustic powers are delivered at closer receivers. It means that acoustic power fades out with larger distances. It is observed that there is a fractional variation of 61%, 17%, 6% and 3% as compared to the receiver 1 for receivers 2, 3, 4 and 5 respectively. Moreover, the results show that variation in total acoustic power is non-linear and higher acoustic powers will be captured for higher velocities. This comparison is done between wind speeds of 10m/s and 15m/s.

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