Estimation of solar resource for vehicle-integrated photovoltaics in urban environments using image-based shade detection

Abstract

Vehicle-Integrated Photovoltaics (VIPV) in urban environments face challenges in accurately estimating solar resource due to dynamic shading effects. This research presents a methodology for evaluating VIPV solar resource by analyzing imagery and detecting shade conditions along driving routes. Street image mapping services and obstacle detection algorithms are utilized to determine the shaded or sunny condition of the vehicle at each point. The approach enables the calculation of solar irradiance, considering direct and diffuse components, and identifies energetically optimal driving routes. The methodology provides valuable insights for optimizing MPPT algorithms and assessing VIPV performance in urban settings. It offers a practical tool for sustainable mobility and renewable energy integration.