Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters

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Authors

Baseer, Mohammed Abdul
Meyer, Josua P.
Rehman, S.
Alam, Md. M.

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Abstract

The wind characteristics of seven locations in Jubail, Saudi Arabia were analysed by using five years of wind data of six sites and three years data of one site at 10 m above ground level (AGL). The highest annual mean wind speed of 4.52 m/s was observed at Industrial area (east) and lowest of 2.52 m/s at Pearl beach with standard deviations of 2.52 and 1.1 m/s respectively. Weibull parameters were estimated using maximum likelihood, least-squares regression method (LSRM) and WAsP algorithm. The most probable and maximum energy carrying wind speed were found by all the three methods. The correlation coefficient (R2 ), root mean square error (RMSE), mean bias error (MBE) and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM followed by WAsP algorithm. The wind power output at all seven sites from five commercially available wind machines of rated power from 1.8 to 3.3 MW showed that Jubail industrial area (east) is most promising. The energy output from a 3 MW wind machine at this site was found to be 11,136 MWh/yr. with a plant capacity factor (PCF) of 41.3%

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Keywords

Wind power, Weibull parameters, Maximum energy carrying wind speed, Most probable wind speed, Least-squares regression method (LSRM), Correlation coefficient (R2), Root mean square error (RMSE), Mean bias error (MBE), Mean bias absolute error (MAE), Plant capacity factor (PCF), Above ground level (AGL)

Sustainable Development Goals

SDG-07: Affordable and clean energy
SDG-13: Climate action
SDG-09: Industry, innovation and infrastructure

Citation

Baseer, MA, Meyer, JP, Rehman, S & Alam, MM 2017, 'Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters', Renewable Energy, vol. 102, pp. 35-49.