Wind Energy Assessment in Forest Areas Using Multi-Source Optimized WRF Model

Accurate wind field simulation in forest areas is crucial for wind energy development but remains challenging for traditional WRF models due to complex terrain and vegetation heterogeneity. This study proposes a multi-source optimization framework integrating seasonal PBL scheme selection, localized leaf area index (LAI) adjustment, and 3DVAR data assimilation to improve WRF performance in forested terrain. The framework was validated using observations at 20 m, 50 m, and 100 m heights in Maoershan forest area. Results show that: (1) PBL schemes exhibit significant seasonal dependence—YSU performs best in spring (unstable conditions), while MYJ shows slight advantages near the surface in winter (stable conditions). (2) Localized LAI correction reduces near-surface wind speed bias by 35% and improves wind direction accuracy by 28%, with stronger effects in summer. (3) 3DVAR assimilation further enhances accuracy, achieving correlation coefficients of 0.869 for wind speed and 0.813 for wind direction, with greater improvements in summer and near the surface. (4) Winter wind power density at 100 m reaches 475 W/m2, 38% higher than summer, indicating stable exploitable resources. The proposed framework provides a replicable methodology for wind field simulation in forest regions worldwide.