SAC: Solar-Aware E-Taxi Fleet Charging Coordination under Dynamic Passenger Mobility

As electric vehicles (EV) gradually replace traditional fuel vehicles and provide transportation services in cities, e.g., electric taxi/bus fleets, solar-powered charging stations with energy storage systems have been deployed in urban areas to provide charging services for EV fleets [1]. The mixture of solar-powered and traditional charging stations brings efficiency challenges to charging stations and reliability challenges to power systems. In this paper, we explore e-taxis' mobility and charging demand flexibility to co-optimize service quality of e-taxi fleets and system cost of charging infrastructures, such as under-utilization of solar power and reliability issues of the power distribution network due to reverse power flow. Specifically, we propose SAC, an e-taxi coordination framework to dispatch e-taxis for charging or serving passengers under spatiotemporal dynamics of renewable energy and passenger mobility. We formulate the e-taxi fleet coordination problem as a multi-criterion mixed-integer linear programming problem. We evaluate our solution with a comprehensive dataset for e-taxi systems and charging infrastructures including 726 e-taxis, 7,228 regular fuel taxis, 37 working charging stations, and 62,100 collected taxi trips per day. Our data-driven evaluation shows that SAC significantly outperforms existing solutions, reducing the total reverse power flow per day by up to 95.3%, while maintaining e-taxi service quality with very small overhead.