Optimal Integration of Electric Vehicle Loads into the Kano Urban Distribution Network

This study analyses the impacts and develops an optimal integration framework for electric vehicle charging loads on the Kano Electricity Distribution Company's urban medium voltage distribution network, anticipating the adoption trajectory of electric two-wheelers, three-wheelers, and buses in the rapidly growing Kano transport sector. Kano State is actively evaluating EV adoption for its public transport fleet and has attracted several EV assembly investment proposals, making distribution network impact assessment an urgent planning requirement for KEDCO. A GIS-referenced load flow model of the KEDCO Kano urban network was constructed and validated against available billing data. EV adoption scenarios for 2025, 2030, and 2035 were developed based on Nigeria's National EV Policy targets and transport sector projections for Kano, translated into spatial charging demand projections mapped to identified charging depot and public charging station locations. Load flow studies assessed bus voltage violations, transformer loading exceedances, and feeder thermal limit violations under each EV scenario with both unmanaged and smart charging profiles. Results indicate that unmanaged EV charging at the projected 2030 adoption level causes transformer overloading at 18 percent of distribution transformers in the modelled central Kano area during the evening peak period. Smart charging with peak shift to the 22:00 to 06:00 overnight period reduces transformer overloading to 4 percent of units without any network reinforcement. Battery swapping stations, which impose brief but very high power demand, require dedicated LV network upgrades at each location. Keywords: electric vehicle integration, distribution network, Kano, smart charging, load management.