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.
@article{arxiv.2605.14282,
title = {Energy Management for Solar-Powered Electric-Bus Charging Station: A Data-Driven Method},
author = {Xiaoting Wang and Supun Amarathunga and Pasan Gunawardena and Gregory Kish and Yunwei and Li},
journal= {arXiv preprint arXiv:2605.14282},
year = {2026}
}
Comments
5 pages, 4 figures. To appear in the IEEE PES General Meeting 2026