Energy Management for Solar-Powered Electric-Bus Charging Station: A Data-Driven Method
For operators of electric bus charging stations, this provides a flexible EMS that handles real-world uncertainties with limited data.
This paper develops a data-driven energy management system for solar-powered electric bus charging stations that handles uncertainties in solar output, electricity prices, and bus state of charge. Case studies with 20 buses show the method effectively manages energy under limited historical data.
This paper presents a flexible energy management system (EMS) for an electric bus charging station (EBCS) that integrates renewable generation, energy storage, and electric bus (EB) charging while accounting for uncertainties in solar PV output, electricity prices, and EB arrival/departure state of charge. A data-driven polynomial chaos expansion surrogate is developed from a limited set of uncertainty samples, and a nonparametric inference method is used to enrich the input data when historical data is limited. Case studies on a solar-powered EBCS with 20 EBs demonstrate the effectiveness of the proposed EMS and data-driven method.