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Evaluation of NWP performance for wind energy resource assessment in Oman

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  • Charabi, Yassine
  • Al-Yahyai, Sultan
  • Gastli, Adel

Abstract

Few studies have been conducted to evaluate the wind energy potential in Oman. All of the published studies were based on ground measurements from weather stations, which provide wind data at 10Â m above the ground. The spatial and temporal coverage of the actual meteorological network in Oman presents some inadequacy with the need of the wind power industry in term of data sets. Currently, these assessments are done on a site-by-site basis, using existing station data and limited on-site monitoring data. A primary task under this research is to supplement existing wind-power potential assessments and develop an enhanced (spatially explicit) inventory of the wind resource across Oman. With the current available computational power, it is possible to use of high resolution numerical weather prediction (NWP) models to provide wind data usable for wind energy resource assessment. This paper evaluates the performance of NWP model data for wind energy application for Oman with a comparison to satellite data. Two models namely HRM and COSMO were used in this study. Suitable model resolution was first selected by evaluating the ability of the models to simulate weak local wind circulation (i.e. sea breeze), then one year of data was generated and compared to satellite data and ground measurements. The NWP data showed better accuracy over satellite data with comparison to the ground measurements. Wind power output was also calculated for selected sites with high potential.

Suggested Citation

  • Charabi, Yassine & Al-Yahyai, Sultan & Gastli, Adel, 2011. "Evaluation of NWP performance for wind energy resource assessment in Oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1545-1555, April.
  • Handle: RePEc:eee:rensus:v:15:y:2011:i:3:p:1545-1555
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    1. Charabi, Yassine & Gastli, Adel, 2010. "GIS assessment of large CSP plant in Duqum, Oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 835-841, February.
    2. Gastli, Adel & Charabi, Yassine, 2010. "Solar electricity prospects in Oman using GIS-based solar radiation maps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 790-797, February.
    3. Gastli, Adel & Charabi, Yassine & Zekri, Slim, 2010. "GIS-based assessment of combined CSP electric power and seawater desalination plant for Duqum--Oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 821-827, February.
    4. AL-Yahyai, Sultan & Charabi, Yassine & Gastli, Adel & Al-Alawi, Saleh, 2010. "Assessment of wind energy potential locations in Oman using data from existing weather stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1428-1436, June.
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    Cited by:

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    6. Al-Badi, A.H. & Malik, A. & Gastli, A., 2011. "Sustainable energy usage in Oman—Opportunities and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3780-3788.
    7. Al-Yahyai, Sultan & Charabi, Yassine, 2015. "Assessment of large-scale wind energy potential in the emerging city of Duqm (Oman)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 438-447.
    8. Zhang, Yagang & Zhang, Jinghui & Yu, Leyi & Pan, Zhiya & Feng, Changyou & Sun, Yiqian & Wang, Fei, 2022. "A short-term wind energy hybrid optimal prediction system with denoising and novel error correction technique," Energy, Elsevier, vol. 254(PC).
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