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

M. A. Baseer*, J. P. Meyer, S. Rehman, Md Mahbub Alam

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

139 Scopus citations

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%.

Original languageEnglish
Pages (from-to)35-49
Number of pages15
JournalRenewable Energy
Volume102
DOIs
StatePublished - 1 Mar 2017

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Ltd

Keywords

  • Maximum energy carrying wind speed
  • Most probable wind speed
  • Plant capacity factor
  • Weibull parameters
  • Wind power

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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