A WRF-PALM Multiscale Approach to Assessing Renewable Climate Resources in High-Density Urban River Valleys

High-density river-valley cities face intensifying heat stress and rising electricity demand, making energy conservation and effective use of renewable resources increasingly imperative. However, wind and solar resources are highly heterogeneous within the urban canopy due to complex terrain and dense morphology, which complicates practical deployment. This study applies a WRF–PALM multiscale modeling framework to quantify future renewable climate resources in Chongqing and to deliver planning-ready micro-siting guidance for hybrid wind–solar streetlights. Bias-corrected CMIP6 forcing under SSP2-4.5 drives mesoscale WRF simulations, and the resulting time-evolving fields are used to force meter-scale PALM large-eddy simulations for both winter and summer. We derive street-level wind and irradiance fields, compute wind and PV capacity factors, and evaluate hybrid energy output across three surface–morphology regimes. Model evaluation indicates that the coupled framework improves near-surface wind and temperature simulations relative to WRF alone. Results show strong seasonality in solar resources and systematic contrasts across regimes: compact high-rise areas exhibit weak within-canopy winds and strong shading, whereas open mid-rise and river-adjacent areas achieve higher PV capacity factors and larger hybrid yields. Using an energy-balance criterion for street lighting, 783 candidate sites in the open mid-rise regime can meet net-zero daily consumption in both seasons. The proposed deployment provides substantial co-benefits, with estimated life-cycle electricity cost savings of about 56.2 million CNY and avoided CO₂ emissions of about 28.1 kt. Overall, we demonstrate that the framework is feasible and offers a transferable pathway from future climate scenarios to actionable, street-scale renewable micro-siting in complex urban terrain.