Utilizing street view images to estimate solar energy potential for photovoltaic-powered buses

Abstract

Photovoltaic-powered buses offer a promising solution for reducing fossil fuel dependency and alleviating pressure on power grids. This study evaluates the solar energy potential in downtown Beijing by utilizing street view images, meteorological data, and advanced analytical techniques, including deep learning and the radiative transfer model. The analysis incorporates spatial characteristics, seasonal variations, and the impact of weather conditions on solar energy availability. Key findings include: (1) downtown Beijing exhibits substantial solar energy potential, with seasonal and spatial variations. Solar energy levels are highest on east-west oriented streets during summer, reaching up to 15.0 MJ/m²/day, while winter levels can drop to as low as 6.0 MJ/m²/day in densely built areas; (2) photovoltaic-powered buses can generate up to 100 kWh per day, enabling annual travel of 88,500 km under clear skies and 64,300 km under cloudy conditions, while reducing carbon emissions by 88.4 tons and 64.3 tons, respectively; (3) integrating photovoltaic systems into public transportation offers significant economic and environmental benefits, enhancing energy security and promoting sustainability. These results demonstrate the feasibility and advantages of incorporating photovoltaic technology into urban public transit, contributing to the development of sustainable cities by reducing carbon emissions and improving energy efficiency.