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Main Authors: Wang, Xiaoting, Amarathunga, Supun, Gunawardena, Pasan, Kish, Gregory, Yunwei, Li
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.14282
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author Wang, Xiaoting
Amarathunga, Supun
Gunawardena, Pasan
Kish, Gregory
Yunwei
Li
author_facet Wang, Xiaoting
Amarathunga, Supun
Gunawardena, Pasan
Kish, Gregory
Yunwei
Li
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2605_14282
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Energy Management for Solar-Powered Electric-Bus Charging Station: A Data-Driven Method
Wang, Xiaoting
Amarathunga, Supun
Gunawardena, Pasan
Kish, Gregory
Yunwei
Li
Systems and Control
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.
title Energy Management for Solar-Powered Electric-Bus Charging Station: A Data-Driven Method
topic Systems and Control
url https://arxiv.org/abs/2605.14282