The Analysis of Wind Power Potential in Sahara Site of Algeria-an Estimation Using the ‘Weibull’ Density Function

Dahbi, M.; Benatiallah, A.; Sellam, M.

doi:10.1016/j.egypro.2013.07.021

Cited by 21 publications

(16 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Firstly, they found the two parameters using yearly wind data and secondly using monthly wind data. The power predictions are performed using monthly scale and shape parameters [13]. Khahro, Tabbassum, Soomro, Dong and Liao investigated the wind power production i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 5 ) 1 e1 0 potential of Babaurband, Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function

Bilir

İmir

Devrim

et al. 2015

International Journal of Hydrogen Energy

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function

Bilir

İmir

Devrim

et al. 2015

International Journal of Hydrogen Energy

View full text Add to dashboard Cite

“…Additionally, the wind energy density (E) can be found by multiplying wind power density by the desired time (T) (for example; a year, a season or a month) [8];…”

Section: Wind Power Density Calculationmentioning

confidence: 99%

“…Wind power density ðPÞ for a region can be found using Weibull parameters along with the following equation [8];…”

Section: Wind Power Density Calculationmentioning

confidence: 99%

See 1 more Smart Citation

An investigation on wind energy potential and small scale wind turbine performance at İncek region – Ankara, Turkey

Bilir

İmir

Devrim

et al. 2015

Energy Conversion and Management

108

View full text Add to dashboard Cite

“…An important factor in evaluating the economic feasibility of a potential wind farm, the WPD can be given in two types as follows [7,18,39]:…”

Section: Wind Power Density (Wpd) Errormentioning

confidence: 99%

Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea

Kang

Huh

2018

Energies

View full text Add to dashboard Cite

On Jeju Island, South Korea, an investigation was conducted to determine the best method for estimating Weibull parameters. Six methods commonly used in many fields of the wind energy industry were reviewed: the empirical, moment, graphical, energy pattern factor, maximum likelihood, and modified maximum likelihood methods. In order to improve the reliability of a research result, five-year actual wind speed data taken from nine sites with various topographical conditions were used for the estimation. Furthermore, the effect of various topographical conditions on the accuracy of the methods was analyzed and 10 bin interval types were applied to determine the most appropriate bin interval based on their performances. Weibull distributions that were estimated using these methods were compared with the observed wind speed distribution. Then the accuracy of each method was evaluated using four accuracy tests. The results showed that of the six methods, the moment method had the best performance regardless of topographical conditions, while the graphical method performed the worst. Additionally, topographical conditions did not affect the accuracy ranking of the methods for estimating the Weibull parameters, while an increase of terrain complexity resulted in an increase of discrepancy between the estimated Weibull distribution and the frequency of the observed wind speed data. In addition, the choice in bin interval greatly affected the accuracy of the graphical method while it did not depend on the accuracy of the modified maximum likelihood method.

show abstract

The Analysis of Wind Power Potential in Sahara Site of Algeria-an Estimation Using the ‘Weibull’ Density Function

Cited by 21 publications

References 9 publications

Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function

Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function

An investigation on wind energy potential and small scale wind turbine performance at İncek region – Ankara, Turkey

Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea

Contact Info

Product

Resources

About