Related Papers
Diagnosis of the Best Method for Wind Speed Extrapolation
Firas Hadi
The standard height of meteorological towers for wind speed observations is 10 meters. Since wind turbine hub heights are typically more than thisheight, extrapolation of wind speeds to the planned hub height is usually required, the most elementary models for predicting the adjusted wind speed are power law and logarithmic law.The purpose of this paper is to extrapolate the wind speed and power density to different heightsusingpowerlaw, logarithmic law,and wind speed distribution extrapolation;thenthe results werecompared with the real data taken from sensors located atdifferentheightsfor the purpose of knowing the best representation method. The sensors are installed at 10, 30, 52 meters heights from ground surface at Al-Shehabi site in Iraq. Also, for more benefits, both of results and the observed data (real data) were compared with wind resource map of Iraq (Geosun) in order to know the accuracy of map’s data. It is found that the wind speed distribution extrapolationgives more acceptable results than the power and logarithmic lawsfor extrapolation procedure, at the same time it was proved that how much extent the validity of map is.
Renewable energy & power quality journal
Insights on the use of wind speed vertical extrapolation methods
2022 •
Rosa Pilão
Journal of Basic & Applied Sciences
Effect of Wind Shear Coefficient for the Vertical Extrapolation of Wind Speed Data and its Impact on the Viability of Wind Energy Project
2015 •
Saif Rehman, Saifuddin Jilani
Statistical Analysis of Wind Speed Data Rüzgar Hiz Veri̇leri̇ni̇n İstati̇sti̇ksel Anali̇zi̇
2005 •
veysel yılmaz
Advances in Meteorology
Wind Velocity Vertical Extrapolation by Extended Power Law
2012 •
Abdusselam Altunkaynak
Wind energy gains more attention day by day as one of the clean renewable energy resources. We predicted wind speed vertical extrapolation by using extended power law. In this study, an extended vertical wind velocity extrapolation formulation is derived on the basis of perturbation theory by considering power law and Weibull wind speed probability distribution function. In the proposed methodology not only the mean values of the wind speeds at different elevations but also their standard deviations and the cross-correlation coefficient between different elevations are taken into consideration. The application of the presented methodology is performed for wind speed measurements at Karaburun/Istanbul, Turkey. At this location, hourly wind speed measurements are available for three different heights above the earth surface.
The impacts of atmospheric stability on the accuracy of wind speed extrapolation methods
Petra Klein
Accuracy of Vertically Extrapolating Meteorological Tower Wind Speed Measurements
William Lubitz
Energy Conversion and Management
Estimating wind speed distribution
2002 •
Atsu Dorvlo
A STATISTICAL APPROACH TO ESTIMATE THE WIND
Veysel YILMAZ
Wind energy is renewable and environment friendly. It is an alternative clear energy source compared to the fossil fuels that pollute the lower layer of atmosphere. The most important parameter of the wind energy is the wind speed. Statistical methods are useful for estimating wind speed because it is a random phenomena. For this reason, wind speed probabilities can be estimated byusing probability distributions. An accurate determination of probability distribution for wind speed values is very important in evaluating wind speed energy potential of a region. In this study, first, we tried to determine appropriate theoretical pdf (probability density function) by comparing 10 pdf for the wind speed data measured for Gelibolu region. In determining proper pdf , an approach consisting of 3 goodness of fit tests and fitted graphics have been used
Approximation of wind speed distributions with theoretical distributions of meteorological stations located in different orographic conditions
2019 •
István Hadnagy
This research analyses the daily average wind speed time series of ten Transcarpathian meteorological stations in the period from 2011 to 2015 with the help of statistical methods. We approximated the empirical frequency distribution of measured daily average wind speeds by means of theoretical distributions. The results of the fitting test showed that among the applied theoretical distributions, irrespective of orographic conditions, the Weibull distribution is proved to be the most suitable. However, fitting the Weibull distribution depends on the methods of determining parameters k and c. By means of the best fitting parameters, the distribution density function and some of its indices at the altitude of 80 m were worked out contrary to the anemometer altitude that is often the hub height of industrial wind turbines, thus estimating the wind conditions of the area from wind energy utilization point of view.
