Urban informatics meets PV physics: The need for spatio-temporal data for global validation of city-aware vehicle-integrated PV models

Achieving significant PV adoption in modern cities requires its incorporation into urban environments, including vehicles occupying its streets. However, it remains uncertain how urban settings impact the energy yield of vehicle-integrated PV (VIPV) systems compared to conventional systems deployed in static surroundings. Recently, we introduced PVMAPS+City, a physics-based model designed to predict the annual energy yield potential of VIPV systems. It leverages spatial information, such as building heights, road widths, and orientations to make city-aware predictions, bridging urban informatics with PV physics. In this study, we tested the model against three real-world vehicle test datasets reported in the literature from three different cities worldwide. In all cases, the model predicted the measured annual yield and mileage with an accuracy of within 5-10% of the measured values. Importantly, the tests highlight the necessity of spatio-temporal information for accurate performance comparisons, as well as for interpreting measured data and validating models. The three datasets offered varying levels of such information. The results demonstrate the model’s value as a powerful and reliable tool for providing realistic estimates of VIPV benefits, aiding in the evaluation of PV integration for future green transportation systems.