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

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dc.contributor.author Baseer, Mohammed Abdul
dc.contributor.author Meyer, Josua P.
dc.contributor.author Rehman, S.
dc.contributor.author Alam, Md. M.
dc.date.accessioned 2017-01-31T08:43:59Z
dc.date.issued 2017-03
dc.description.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% en_ZA
dc.description.department Mechanical and Aeronautical Engineering en_ZA
dc.description.embargo 2018-03-31
dc.description.librarian hb2017 en_ZA
dc.description.sponsorship The Research Grant Council of Shenzhen Government through grant KQCX2014052114423867. en_ZA
dc.description.uri http://www.elsevier.com/locate/renene en_ZA
dc.identifier.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. en_ZA
dc.identifier.issn 0960-1481 (print)
dc.identifier.issn 1879-0682 (online)
dc.identifier.other 10.1016/j.renene.2016.10.040
dc.identifier.uri http://hdl.handle.net/2263/58721
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2016 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Renewable Energy, vol. 102, pp. 35-49, 2017. doi : 10.1016/j.renene.2016.10.040. en_ZA
dc.subject Wind power en_ZA
dc.subject Weibull parameters en_ZA
dc.subject Maximum energy carrying wind speed en_ZA
dc.subject Most probable wind speed en_ZA
dc.subject Least-squares regression method (LSRM) en_ZA
dc.subject Correlation coefficient (R2) en_ZA
dc.subject Root mean square error (RMSE) en_ZA
dc.subject Mean bias error (MBE) en_ZA
dc.subject Mean bias absolute error (MAE) en_ZA
dc.subject Plant capacity factor (PCF) en_ZA
dc.subject Above ground level (AGL) en_ZA
dc.subject.other Engineering, built environment and information technology articles SDG-07
dc.subject.other SDG-07: Affordable and clean energy
dc.subject.other Engineering, built environment and information technology articles SDG-13
dc.subject.other SDG-13: Climate action
dc.subject.other Engineering, built environment and information technology articles SDG-09
dc.subject.other SDG-09: Industry, innovation and infrastructure
dc.title Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters en_ZA
dc.type Postprint Article en_ZA


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