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A hybrid method integrating the Weather Research and Forecasting (WRF) model and computational fluid dynamics (CFD) was developed to evaluate wind resources in Liaoning Province, China. The WRF model first simulated annual mean wind speeds at a 3 km × 3 km resolution, providing boundary conditions for the CFD model. Using the Reynolds-averaged Navier–Stokes equations with the realisable k–ε turbulence model, CFD refined the results to 1 km × 1 km accuracy, accounting for complex terrain effects. Wind-power density was calculated via conversion formulas, enabling analysis of wind energy reserves and technical exploitable potential. At 70 m height, Liaoning’s land area exhibits a technical exploitable capacity of 593 346 MW, with high-wind zones concentrated along the Circum-Bohai-Sea shoreline, northwestern mountainous regions, Changbai Mountain’s main ridge, and central plains. The study validates the WRF-CFD coupling approach, demonstrating its efficacy in downscaling coarse WRF outputs to high-resolution grids through CFD terrain correction. This method provides spatially refined wind resource data, critical for optimising wind farm siting and supporting regional energy planning. Key advantages include enhanced accuracy in complex topography and scalable grid resolution, offering actionable insights for sustainable wind energy development.

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