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 |