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Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment

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

Abstract

Wind energy resource assessment applications require accurate wind measurements. Most of the published studies used data from existing weather station network operated by meteorological departments. Due to relatively high cost of weather stations the resolution of the weather station network is coarse for wind energy applications. Typically, meteorological departments install weather stations at specific locations such as airports, ports and areas with high density population. Typically, these locations are avoided during wind farms siting. According to WMO regulations, weather stations provide measurements for different weather elements at specific altitudes such as 2Â m for air temperature and 10Â m for wind measurements. For wind energy resource assessment applications, minimum of one year of wind measurements is required to build wind climatology for a certain site. Therefore data collected from a certain site cannot be used before one year of operation. Due to these limitations, wind energy resource assessment application needs to use data from different sources. Recently, wind assessment studies were conducted using data generated by Numerical Weather Prediction models. This paper reviews the use of the Numerical Weather Prediction data for wind energy resource assessment. It gives a general overview of NWP models and how they overcome the limitations in the classical wind measurements.

Suggested Citation

  • Al-Yahyai, Sultan & Charabi, Yassine & Gastli, Adel, 2010. "Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3192-3198, December.
  • Handle: RePEc:eee:rensus:v:14:y:2010:i:9:p:3192-3198
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    References listed on IDEAS

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    1. Dorvlo, A.S.S & Ampratwum, D.B, 2002. "Wind energy potential for Oman," Renewable Energy, Elsevier, vol. 26(3), pages 333-338.
    2. Ucar, Aynur & Balo, Figen, 2009. "Evaluation of wind energy potential and electricity generation at six locations in Turkey," Applied Energy, Elsevier, vol. 86(10), pages 1864-1872, October.
    3. Radics, Kornélia & Bartholy, Judit, 2008. "Estimating and modelling the wind resource of Hungary," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(3), pages 874-882, April.
    4. Sulaiman, M.Yusof & Akaak, Ahmed Mohammed & Wahab, Mahdi Abd & Zakaria, Azmi & Sulaiman, Z.Abidin & Suradi, Jamil, 2002. "Wind characteristics of Oman," Energy, Elsevier, vol. 27(1), pages 35-46.
    5. AfDB AfDB, . "AfDB Group Annual Report 2008," Annual Report, African Development Bank, number 64 edited by Koua Louis Kouakou.
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