Evaluation and Improvement of the Accuracy of Reanalysis and Analysis Datasets for Wind Resource Assessment in Sudan

Authors

  • Youssef Kassem Department of Mechanical Engineering, Engineering Faculty, Near East University, Cyprus | Energy, Environment, and Water Research Center, Near East University, Cyprus | Science, Technology, Engineering Education Application and Research Center, Near East University, Cyprus
  • Huseyin Camur Department of Mechanical Engineering, Engineering Faculty, Near East University, Cyprus | Science, Technology, Engineering Education Application and Research Center, Near East University, Cyprus
  • Mohamedalmojtba Hamid Ali Abdalla Department of Mechanical Engineering, Engineering Faculty, Near East University, Cyprus
Volume: 14 | Issue: 2 | Pages: 13741-13750 | April 2024 | https://doi.org/10.48084/etasr.7035

Abstract

Wind speed datasets are used to evaluate wind resources and energy production of wind farms. In locations where measured data are not available, reanalysis and analysis datasets can be used as an alternative to assess wind resources. This study evaluated the accuracy of wind speed data collected from reanalysis and analysis datasets against mast-measured data between 1975 and 1985 in Sudan, using monthly statistical analyses. Three bias correction methods, based on Measure-Correlate-Predict (MCP) and Linear Adaptation (LA1 and LA2), were applied to determine the original wind speed. The results indicate that LA1 outperformed MCP and LA2. Furthermore, the Weibull distribution function was employed to analyze the wind speed characteristics. In addition, wind power density was calculated using data from different sources. The findings show that although the wind power potential of the chosen locations is not suitable for large wind turbines, wind power can still be exploited with small wind turbines. Consequently, this study introduces a wind energy roadmap to attract investors in clean energy for sustainable development in Sudan, address energy problems, and meet domestic demands. The study also identifies the most important grid datasets for assessing the country's wind potential, enhancing the accuracy of assessments for investors and policymakers.

Keywords:

Sudan, mast measurement, bias correction methods, reanalysis and analysis datasets, wind energy potential

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[1]
Kassem, Y., Camur, H. and Abdalla, M.H.A. 2024. Evaluation and Improvement of the Accuracy of Reanalysis and Analysis Datasets for Wind Resource Assessment in Sudan. Engineering, Technology & Applied Science Research. 14, 2 (Apr. 2024), 13741–13750. DOI:https://doi.org/10.48084/etasr.7035.

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