Potentiometry of wind, solar and geothermal energy resources and their future perspectives in Iran

Zahedi, Rahim; Sadeghitabar, Erfan; Khazaee, Mehrzad; Faryadras, Reza; Ahmadi, Abolfazl

doi:10.1007/s10668-024-04633-2

Cited by 5 publications

(1 citation statement)

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“…The optimization and evaluation of the WRF model for wind energy resource assessment and mapping in Iran hold significant industrial relevance within the renewable energy sector [121]. The region possesses vast untapped potential for wind energy development, but accurate assessment of wind resources is a crucial step for successful project planning, financing, and operation [122][123][124]. Through the optimization of the WRF model specifically for the Iranian territory, we can improve the accuracy of wind resource assessment and provide valuable insights into the spatial distribution and variability of wind energy resources.…”

Section: Evaluation Of the Wrf Simulationsmentioning

confidence: 99%

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

Saadatabadi,

Hamzeh,

Kaskaoutis

et al. 2024

Applied Sciences

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This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

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