This study presents a scalable framework for estimating solar energy yield from vehicle-integrated photovoltaics (VIPV) on electric buses in dynamic urban environments. It combines semantic 3D CityGML models, distributed PostGIS/Citus processing, CAMS solar data, and high-resolution GTFS trajectories. Direct, diffuse, and reflected radiation are calculated through ray-casting and geometry-based methods, enabling surface-specific assessment of urban shading and reflection. The framework is coupled with the VECTO vehicle energy model to evaluate PV yield against energy consumption. Results show that urban shading can reduce irradiation by more than 20%, while VIPV can cover approximately 2.8–4.1% of annual energy demand for typical electric bus operations. Prior validation using vehicle-mounted sensors confirmed that the 3D approach outperforms conventional 2.5D DSM methods. The distributed architecture supports fleet-scale simulations and integration into CityGML digital twins through Dynamizer, providing a transferable tool for sustainable mobility planning.