Weibull parameters estimation using four different methods and most energy-carrying wind speed analysis

Haralambos S. Bagiorgas; Mihalakakou Giouli; Shafiqur Rehman; Luai M. Al-Hadhrami

doi:10.1080/15435075.2011.588767

Weibull parameters estimation using four different methods and most energy-carrying wind speed analysis

Haralambos S. Bagiorgas^*
, Mihalakakou Giouli
, Shafiqur Rehman
, Luai M. Al-Hadhrami

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

53 Scopus citations

Abstract

The study presents the analysis of wind speed data from seven stations in Saudi Arabia, measured at 20, 30, and 40 m height above ground level (AGL) over a period varying from 2 to 5 years. Specifically, Weibull parameters were calculated using five different methods, four of them based on the statistical analysis of the collected data and a fifth one based on WAsP algorithm used in WindoGrapher software. The calculated values using the five different methods were found to be in good agreement at all the measurement heights. The correlation between the monthly mean values of Weibull scale parameter and the measured wind speed values was found to be linear for all the sites. The linear coefficient 'a' was found to be site's characteristic value and independent of the height AGL for most of the locations. Moreover, linearity has been substantiated between the monthly mean wind power density (WPD) and the corresponding measured wind speed for all the stations, with linear coefficients 'a' directly proportional to height AGL. Finally, the values of Weibull shape parameter (k) were found to be independent of height AGL, while that of scale parameter (c) varying with height.

Original language	English
Pages (from-to)	529-554
Number of pages	26
Journal	International Journal of Green Energy
Volume	8
Issue number	5
DOIs	https://doi.org/10.1080/15435075.2011.588767
State	Published - Jul 2011

Bibliographical note

Funding Information:
The authors would like to acknowledge the support of the Department of Environmental and Natural Resources Management, University of Ioannina, Seferi 2, 30100 Agrinio, Greece, and the Center for Engineering Research, Research Institute, King Fahd University of Petroleum and Minerals, KFUPM Box 767, Dhahran-31261, Saudi Arabia.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Maximum energy-carrying wind speed
Most probable wind speed
Scale parameter (c)
Shape parameter (k)
Weibull distribution

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment

Access to Document

10.1080/15435075.2011.588767

Cite this

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title = "Weibull parameters estimation using four different methods and most energy-carrying wind speed analysis",

abstract = "The study presents the analysis of wind speed data from seven stations in Saudi Arabia, measured at 20, 30, and 40 m height above ground level (AGL) over a period varying from 2 to 5 years. Specifically, Weibull parameters were calculated using five different methods, four of them based on the statistical analysis of the collected data and a fifth one based on WAsP algorithm used in WindoGrapher software. The calculated values using the five different methods were found to be in good agreement at all the measurement heights. The correlation between the monthly mean values of Weibull scale parameter and the measured wind speed values was found to be linear for all the sites. The linear coefficient 'a' was found to be site's characteristic value and independent of the height AGL for most of the locations. Moreover, linearity has been substantiated between the monthly mean wind power density (WPD) and the corresponding measured wind speed for all the stations, with linear coefficients 'a' directly proportional to height AGL. Finally, the values of Weibull shape parameter (k) were found to be independent of height AGL, while that of scale parameter (c) varying with height.",

keywords = "Maximum energy-carrying wind speed, Most probable wind speed, Scale parameter (c), Shape parameter (k), Weibull distribution",

author = "Bagiorgas, \{Haralambos S.\} and Mihalakakou Giouli and Shafiqur Rehman and Al-Hadhrami, \{Luai M.\}",

note = "Funding Information: The authors would like to acknowledge the support of the Department of Environmental and Natural Resources Management, University of Ioannina, Seferi 2, 30100 Agrinio, Greece, and the Center for Engineering Research, Research Institute, King Fahd University of Petroleum and Minerals, KFUPM Box 767, Dhahran-31261, Saudi Arabia.",

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N2 - The study presents the analysis of wind speed data from seven stations in Saudi Arabia, measured at 20, 30, and 40 m height above ground level (AGL) over a period varying from 2 to 5 years. Specifically, Weibull parameters were calculated using five different methods, four of them based on the statistical analysis of the collected data and a fifth one based on WAsP algorithm used in WindoGrapher software. The calculated values using the five different methods were found to be in good agreement at all the measurement heights. The correlation between the monthly mean values of Weibull scale parameter and the measured wind speed values was found to be linear for all the sites. The linear coefficient 'a' was found to be site's characteristic value and independent of the height AGL for most of the locations. Moreover, linearity has been substantiated between the monthly mean wind power density (WPD) and the corresponding measured wind speed for all the stations, with linear coefficients 'a' directly proportional to height AGL. Finally, the values of Weibull shape parameter (k) were found to be independent of height AGL, while that of scale parameter (c) varying with height.

AB - The study presents the analysis of wind speed data from seven stations in Saudi Arabia, measured at 20, 30, and 40 m height above ground level (AGL) over a period varying from 2 to 5 years. Specifically, Weibull parameters were calculated using five different methods, four of them based on the statistical analysis of the collected data and a fifth one based on WAsP algorithm used in WindoGrapher software. The calculated values using the five different methods were found to be in good agreement at all the measurement heights. The correlation between the monthly mean values of Weibull scale parameter and the measured wind speed values was found to be linear for all the sites. The linear coefficient 'a' was found to be site's characteristic value and independent of the height AGL for most of the locations. Moreover, linearity has been substantiated between the monthly mean wind power density (WPD) and the corresponding measured wind speed for all the stations, with linear coefficients 'a' directly proportional to height AGL. Finally, the values of Weibull shape parameter (k) were found to be independent of height AGL, while that of scale parameter (c) varying with height.

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KW - Shape parameter (k)

KW - Weibull distribution

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Weibull parameters estimation using four different methods and most energy-carrying wind speed analysis

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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