Calculation of Weibull Distribution parameters at low wind speed and performance analysis

In this study, the compatibility of the real wind energy potential to the estimated wind energy potential by Weibull Distribution Function (WDF) of a region with low average wind speed potential was examined. The main purpose of this study is to examine the performance of six different methods used to find the coefficients of the WDF and to determine the best performing method for selected region. In this study seven-year hourly wind speed data obtained from the general directorate of meteorology of this region was used. The root mean square error (RMSE) statistical indicator was used to compare the efficiency of all used methods. Another main purpose of this study is to observe the how the performance of the used methods changes over the years. The obtained results showed that the performances of the used methods showed slight changes over the years, but when evaluated in general, it was observed that all method showed acceptable performance. Based on the obtained results, when the seven-year data is evaluated in this selected region, it can be said that the MM method shows the best performance.

Evaluation of projected decadal wind energy potential in Chiang Mai

One of the alternative energy sources which have globally pay more attention is wind power. In this research, the Weibull wind speed distribution was applied to evaluate wind energy potential during the period of 2081-2090. The projected wind datasets in this study were simulated by the Non hydrostatic Regional Climate Model (NHRCM). The boundary condition was the 20 km resolution MRI Atmospheric General Circulation Model (AGCM20) under the RCP8.5 scenario. The surface wind datasets in Chiang Mai were analyzed to 3-time intervals, i.e., May-August, September-December and January-April. Two averaged Weibull distribution parameters, i.e., k, shape parameter, and c, scale parameter were determined. The shape and scale parameters fluctuated 1.15 to 1.34 and 0.38 m/s to 0.74 m/s, respectively. It was found that the surface mean wind speed from May through August was stronger than from September through December.

The Application of Small-Scale and Large-Scale Wind Turbines in Kerman, Iran; A Case Study

Wind data collected of the three synoptic sites for the period of Jul 2006 to Jun 2008 at the height of 40 m has been used to study the wind characteristics, monthly and annual wind energy potential for three agricultural districts in Kerman ( 30°15/N, 56°58/E ), Iran. Two statistical methods (Meteorological and Weibull) have been applied to determine the wind characteristics. Wind energy density, mean wind speeds and wind speed directions have been investigated. A technical assessment has been done and the electricity generation from five different wind turbines having capacity of (26 kW, 100 kW, 300 kW, 600 kW and 660 kW) has been calculated. The results show that all the locations studied are not suitable for electric wind application in a large-scale.

Estimation of the Wind Energy Potential in Various North Algerian Regions

This investigation aims to model and assess the wind potential available in seven specific regions of North Algeria. These regions, i.e., Batna, Guelma, Medea, Meliana, Chlef, Tiaret, and Tlemcen, are known for their traditional agriculture. The wind data are obtained from the National Agency of Meteorology (NAM), and a Weibull distribution is applied. In the first part of this study, the wind potential available in these sites is assessed. Then, different models are used to estimate the wind system’s annual recoverable energy for these regions. We are interested in wind pumping for possible use to meet the needs of irrigation water in rural areas. Four kinds of wind turbines are explored to determine the possibility of wind energy conversion. In addition, the effects of the heights of the pylon holding the turbines are inspected by considering four cases (10, 20, 40, and 60 m). This estimation showed that the annual mean wind velocity varies from 2.48 to 5.60 m/s at a level of 10 m. The yearly values of Weibull parameters (k and c) at the studied sites varied within 1.61–2.43 and 3.32–6.20 m/s, respectively. The average wind power density ranged from 11.48 (at Chlef) to 238.43 W/m2 (at Tiaret), and the monthly wind recoverable potential varied from 16.64 to 138 W/m2.

Statistical analysis of measured wind speed data’s appealing spreadsheet applications

Once the wind data is measured, the values are processed, based on statistic approach, as accurately as possible, to provide a clear over-view of the locations wind potential, being the basis of any wind farm project, representing the go or no-go in further subsequent design steps. The probability density distributions are derived from time-series data, identifying the associated distributional parameters. The wind energy potential of the locations is studied based on the Rayleigh and Weibull models, implemented with the help of Excel computations, and representing tools, to understand the wind characteristics. Based on the statistical analysis of wind conditions presented here, the results of current study can be used to make a sustainable energy yield for any location.