Wind Field Modeling over Hilly Terrain: A Review of Methods, Challenges, Limitations, and Future Directions

Abstract

Accurate wind field modeling over hilly terrain is critical for wind energy, infrastructure safety, and environmental assessment, yet its inherent complexity poses significant simulation challenges. This paper systematically reviews this field’s major advances by analyzing 610 key publications from 2015 to 2024, selected from core databases (e.g., Web of Science and Scopus) through targeted keyword searches (e.g., ‘wind flow’, ‘complex terrain’, ‘CFD’, ‘hilly’) and subsequent rigorous relevance screening. We critique four primary modeling paradigms—field measurements, wind tunnel experiments, Computational Fluid Dynamics (CFD), and data-driven methods—across three key application areas, filling a gap left by previous single-focus reviews. The analysis confirms CFD’s dominance (75% of studies), with a clear shift from idealized 2D to real 3D terrain. Key findings indicate that high-fidelity coupled models (e.g., LES), validated against benchmark field experiments such as Perdigão, can reduce mean wind speed prediction bias to below 0.1 m/s; and optimized engineering designs for mountainous infrastructure can mitigate local wind speed amplification effects by 15–20%. Data-driven surrogate models, represented by FuXi-CFD, show revolutionary potential, reducing the inference time for high-resolution wind fields from hours to seconds, though they currently lack standardized validation. Finally, this review summarizes persistent challenges and outlines future directions, advocating for physics-informed neural networks, high-fidelity multi-scale models, and the establishment of open-access benchmark datasets.