Spatiotemporal Assessment of Solar Powered EV Charging Infrastructure: A Case Study of Kampala-Wakiso Area in Uganda

The rapid adoption of electric vehicles (EVs) creates a planning challenge for the Kampala-Wakiso metropolitan region in Uganda, where the electricity grid already faces local network constraints. This study applies the EVPV-Simulator, an open-source geospatial modelling framework that links mobility demand, charging demand, and EV-PV complementarity, to assess projected charging demand and solar integration potential in the Kampala-Wakiso metropolitan region. By simulating the charging requirements of a projected fleet of 60,000 EVs, the study identifies a pronounced evening charging peak concentrated in residential areas and weakly aligned with daytime solar availability. Under the base-case charging pattern, increasing PV capacity raises the self-sufficiency potential, but has limited influence on the evening peak. In the base-case with 40 MW of installed PV capacity, the self-sufficiency ratio reaches 39.6%, while peak demand falls by only 0.20%. A charging location sensitivity analysis then shows that temporal alignment improves substantially when charging shifts from home towards workplaces and Points of Interest (POI). In a selected daytime oriented scenario with 40% workplace charging and 60% POI charging, the self-sufficiency potential reaches 68.97% and the mean daily maximum net load falls to about 18 MW at 40 MW of installed PV capacity. These results show that the value of solar integration depends strongly on where charging occurs, and that daytime charging access should be treated as a central variable in EV infrastructure planning. The study provides a planning oriented basis for future work incorporating feeder level validation, explicit PV siting constraints, and storage.