Extreme Gust Loading for Wind Turbines during Operation

2001 ◽  
Vol 123 (4) ◽  
pp. 356-363 ◽  
Author(s):  
P. W. Cheng ◽  
W. A. A. M. Bierbooms
Keyword(s):  
Wind Speed ◽  
Theoretical Method ◽  
Rational Approach ◽  
Reliable Estimate ◽  
International Electrotechnical Commission ◽  
Response Distribution ◽  
Statistical Parameters ◽  
Extreme Load ◽  
Mean Wind Speed ◽  
Gust Response

One of the extreme load cases treated in the wind turbine certification is the extreme gust loading during operation. In the certification codes, it is treated in a deterministic way. A method of generating stochastic extreme gusts that includes the turbulence properties of the wind is described in this paper. For the moment, only the horizontal along wind direction of the wind speed is considered. The stochastic gusts are used to determine the gust responses. The gust responses are processed together with the probability density of the gust amplitude and mean wind speed to obtain the gust response distribution. Different distribution types, namely Rayleigh, Weibull, and Gumbel distributions, are applied to fit the distribution of the extreme gust responses. The estimated distributions are analyzed with statistical methods to determine the required number of simulations to obtain a reliable estimate of the statistical parameters of the distribution. The resulting structural responses to the stochastic gusts are compared to the gust response to the extreme operating gust specified in the IEC (International Electrotechnical Commission) design standard. The results show that the extreme gust response can differ significantly depending on the control concept. The response of the deterministic gust proposed in the IEC design code can also deviate considerably from the response of the stochastic gust depending on the turbine configuration. The aim of this work is to provide a rational approach to determine the extreme gust response. This theoretical method has not yet been verified with extensive measurements.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

scholarly journals The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters

2018 ◽  
Vol 7 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Adekunlé Akim Salami ◽  
Ayité Sénah Akoda Ajavon ◽  
Mawugno Koffi Kodjo ◽  
Seydou Ouedraogo ◽  
Koffi-Sa Bédja
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Time Series Data ◽  
Empirical Method ◽  
Likelihood Method ◽  
Series Data ◽  
New Approach ◽  
Weibull Parameters ◽  
Distribution Histogram ◽  
Mean Wind Speed

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

Stochastic generation of hourly mean wind speed data

2004 ◽  
Vol 29 (14) ◽  
pp. 2111-2131 ◽  
Author(s):  
Hafzullah Aksoy ◽  
Z Fuat Toprak ◽  
Ali Aytek ◽  
N Erdem Ünal
Keyword(s):  
Wind Speed ◽  
Stochastic Generation ◽  
Wind Speed Data ◽  
Mean Wind Speed

Scale and Lag Effects on Control of Aerodynamic Power and Loads on a HAWT Rotor

2001 ◽  
Vol 123 (4) ◽  
pp. 339-345 ◽  
Author(s):  
P. J. Moriarty ◽  
A. J. Eggers, ◽  
K. Chaney ◽  
W. E. Holley
Keyword(s):  
Control System ◽  
Fatigue Life ◽  
Wind Speed ◽  
Open Loop ◽  
Time Lags ◽  
Large Power ◽  
Lag Effects ◽  
Mean Wind Speed ◽  
The Mean ◽  
High Control

The effects of rotor scale and control system lag were examined for a variable-speed wind turbine. The scale study was performed on a teetered rotor with radii ranging between 22.5m and 33.75m. A 50% increase in radius more than doubled the rated power and annual energy capture. Using blade pitch to actively control fluctuating flatwise moments allowed for significant reductions in blade mass for a fixed fatigue life. A blade operated in closed-loop mode with a 33.75m radius weighed less than an open-loop blade with a 22.5m radius while maintaining the same fatigue life of 5×109 rotations. Actuator lag reduced the effectiveness of the control system. However, 50% reductions in blade mass were possible even when implementing a relatively slow actuator with a 1 sec. time constant. Other practical limits on blade mass may include fatigue from start/stop cycles, non-uniform turbulence, tower wake effects, and wind shear. The more aggressive control systems were found to have high control accelerations near 60 deg/s2, which may be excessive for realistic actuators. Two time lags were introduced into the control system when mean wind speed was estimated in a rapidly changing wind environment. The first lag was the length of time needed to determine mean wind speed, and therefore the mean control settings. The second was the frequency at which these mean control settings were changed. Preliminary results indicate that quickly changing the mean settings (every 10 seconds) and using a moderate length mean averaging time (60 seconds) resulted in the longest fatigue life. It was discovered that large power fluctuations occurred during open-loop operation which could cause sizeable damage to a realistic turbine generator. These fluctuations are reduced by one half or more when aerodynamic loads are actively controlled.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

scholarly journals Climatological Features of the Weakly and Very Stably Stratified Nocturnal Boundary Layers. Part I: State Variables Containing Information about Regime Occupation

2019 ◽  
Vol 76 (11) ◽  
pp. 3455-3484 ◽  
Author(s):  
Carsten Abraham ◽  
Adam H. Monahan
Keyword(s):  
Wind Speed ◽  
Turbulence Intensity ◽  
Three Dimensional ◽  
Static Stability ◽  
Wind Component ◽  
State Variables ◽  
Intermittent Turbulence ◽  
Additional Information ◽  
State Variable ◽  
Mean Wind Speed

Abstract The atmospheric nocturnal stable boundary layer (SBL) can be classified into two distinct regimes: the weakly SBL (wSBL) with sustained turbulence and the very SBL (vSBL) with weak and intermittent turbulence. A hidden Markov model (HMM) analysis of the three-dimensional state-variable space of Reynolds-averaged mean dry static stability, mean wind speed, and wind speed shear is used to classify the SBL into these two regimes at nine different tower sites, in order to study long-term regime occupation and transition statistics. Both Reynolds-averaged mean data and measures of turbulence intensity (eddy variances) are separated in a physically meaningful way. In particular, fluctuations of the vertical wind component are found to be much smaller in the vSBL than in the wSBL. HMM analyses of these data using more than two SBL regimes do not result in robust results across measurement locations. To identify which meteorological state variables carry the information about regime occupation, the HMM analyses are repeated using different state-variable subsets. Reynolds-averaged measures of turbulence intensity (such as turbulence kinetic energy) at any observed altitude hold almost the same information as the original set, without adding any additional information. In contrast, both stratification and shear depend on surface information to capture regime transitions accurately. Use of information only in the bottom 10 m of the atmosphere is sufficient for HMM analyses to capture important information about regime occupation and transition statistics. It follows that the commonly measured 10-m wind speed is potentially a good indicator of regime occupation.

Diurnal variation in surface latent heat flux and the effect of diurnal variability on the climatological latent heat flux over the tropical oceans

2021 ◽  
Author(s):  
Yunwei Yan ◽  
Lei Zhang ◽  
Xiangzhou Song ◽  
Guihua Wang ◽  
Changlin Chen
Keyword(s):  
Heat Flux ◽  
Wind Speed ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Warm Pool ◽  
Diurnal Variability ◽  
Tropical Oceans ◽  
Mean Wind Speed

AbstractDiurnal variation in surface latent heat flux (LHF) and the effects of diurnal variations in LHF-related variables on the climatological LHF are examined using observations from the Global Tropical Moored Buoy Array. The estimated amplitude of the climatological diurnal LHF over the Indo-Pacific warm pool and the equatorial Pacific and Atlantic cold tongues is remarkable, with maximum values exceeding 20.0 W m−2. Diurnal variability of sea surface skin temperature (SSTskin) is the primary contributor to the diurnal LHF amplitude. Because the diurnal SSTskin amplitude has an inverse relationship with surface wind speed over the tropical oceans, an inverse spatial pattern between the diurnal LHF amplitude and surface wind speed results. Resolving diurnal variations in the SSTskin and wind improves the estimate of the climatological LHF by properly capturing the daytime SSTskin and daily mean wind speed, respectively. The diurnal SSTskin-associated contribution is large over the warm pool and equatorial cold tongues where low wind speeds tend to cause strong diurnal SSTskin warming, while the magnitude associated with the diurnal winds is large over the highly dynamic environment of the Inter-Tropical Convergence Zone. The total diurnal contribution is about 9.0 W m−2 on average over the buoy sites. There appears to be a power function (linear) relationship between the diurnal SSTskin-associated (wind-associated) contribution and surface mean wind speed (wind speed enhancement from diurnal variability). The total contribution from diurnal variability can be estimated accurately from high-frequency surface wind measurements using these relationships.

scholarly journals Evaluation of the Wind Potential and Optimal Design of a Wind Farm in The Arzew Industrial Zone in Western Algeria

2020 ◽  
Vol 9 (2) ◽  
pp. 177-187
Author(s):  
Salah Marih ◽  
Leila Ghomri ◽  
Benaissa Bekkouche
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Clean Energy ◽  
Appropriate Technology ◽  
Environmental Study ◽  
Net Energy ◽  
Electricity Grid ◽  
Wind Potential ◽  
Mean Wind Speed

This work presents an assessment of the wind potential and a design methodology for a 10 MW wind farm in the Arzew industrial region, located in northwest Algeria, to improve the quality of service of the electricity grid and increase Algeria's participation in the use of renewable energy. The hourly wind data of 10 years (2005-2015) that correspond to the wind potential of the site were analyzed, such as: dominant wind directions, probability distribution, Weibull parameters, mean wind speed and power potential. The site has a mean annual wind speed of 4.46 m/s at 10m height, and enough space to locate the wind turbines. A comparative study was carried out between four wind turbine technologies to improve the site's efficiency and select the appropriate technology: PowerWind 56/ 900 kW, Nordex N50/800 kW, Vestas V50/850 kW, NEG-Micon 44/750 kW. The estimate of the energy produced using WAsP software and the choice of the optimal architectural configuration for wind turbines installation was confirmed. A techno-economic and environmental study was carried out by HOMER software, to choose the model that produces the maximum annual net energy with a competitive cost in the global wind energy market, $ 0.068/kWh, and that provides clean energy with a reduced emission of polluting gases. Finally, this work provides a good indicator for the construction of a wind farm in Arzew. ©2020. CBIORE-IJRED. All rights reserved

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