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December 4, 2025Atmosphere4 citationsOpen Access

High-Resolution Assessment of Wind Energy Potential and Operational Risks in Complex Mountain-Basin Systems

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ZWZhiding WuJDJun DaiLBLei Bai

Key Points

  • Wind energy potential varies greatly across complex topographies, revealing significant disparities in resource availability.
  • The study found that the Extreme Wind region has a wind power density 24 times greater than the sheltered Basin.
  • Analysis utilized a 40-year WRF dataset to assess risks and potentials for wind energy generation in Sichuan.
  • The findings suggest adapting strategies for distributed generation can optimize resource use and address operational risks.

Abstract

Conventional wind resource assessments often fail to capture the complex interaction between topography and technology suitability in mountainous regions. This study employs a 40-year, 5 km resolution WRF dataset to construct a differentiated assessment framework for Sichuan Province, distinguishing between utility-scale and distributed generation potentials. The results reveal that topography dictates a stark west-to-east resource gradient, with the Extreme Wind (EW) region possessing a wind power density (1166 W/m2) exceeding that of the sheltered Basin by over 24 times. However, this high potential is coupled with severe operational risks, as overspeed shutdown durations (>25 m/s) in the EW region exceed those in the High Wind Plateau by more than 4.45 times. Crucially, shifting to a distributed generation perspective (2–15 m/s) fundamentally reconstructs the resource landscape: the Basin gains a substantial “light breeze dividend” with available hours increasing by ~89%, whereas the EW region suffers a “high-speed penalty” of ~7% due to frequent cut-out events. Despite a systematic model bias attributed to the “representativeness mismatch” between ridge-resolving grids and valley-bottom observations, the revealed relative spatiotemporal patterns remain robust.

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Cite This Study

Wu et al. (2025) studied this question.

synapsesocial.com/papers/6930dc8aea1aef094cca2753https://doi.org/10.3390/atmos16121362
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