Electric Bus Demand Management through Unidirectional Smart Charging

Darii, Nicolae; Turri, Roberto; Sunderland, Keith

doi:10.1109/upec55022.2022.9917805

Cited by 1 publication

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“…In this regard, EBs offer a peak shaving or load levelling service, which might be included in an Ancillary Service Market or subsidized by the Government to make it competitive and easy for the CS [15]. This study, which is an expanded version of our work that was published at the 57th International Universities Power Engineering Conference [16], concentrated on a Smart-Charging (SC) algorithm that makes use of demand data from the Day-Ahead-Electricity-Market (DAEM). The algorithm provides a Load Leveling or Peak Shaving service by managing the current absorbed by each EB in a Charging Station (CS), while satisfying the charging requirements of the EBs and adhering to a reasonable connection pattern defined by the fleet limit of the EBs.…”

Section: Introductionmentioning

confidence: 99%

A Novel Unidirectional Smart Charging Management Algorithm for Electric Buses

et al. 2023

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The difficulty of controlling the charging of electric buses (EBs) and their effects on network demand are discussed in this study. The solutions suggest a call for worldwide, complex infrastructures that manage EVs and EBs equally. Additionally, the Distribution Network (DN) must be prepared for an increased prevalence of reverse power flow caused by widespread distributed renewable generation. This paper focuses exclusively on EBs since they have higher capacity and predictable charging patterns, which makes them more significant for the DN in the context of a transition to complete vehicle electrification and technologies that are mature enough to be hosted. The proposed algorithm employs the Day-Ahead Energy Market (DAEM) in the Smart Charging (SC) to forecast the network operating circumstances. Additionally, the technique makes it possible to facilitate distributed photovoltaic (PV) generation, allowing network demand to be referenced depending on net demand. It also identifies an appropriate individual charger current per vehicle and per-time-step with load-levelling or peak-shaving as its primary goal. The final real demand demonstrates that a coarse correction of the demand is possible. According to the analysis of the DN voltage profile and associated line losses, the ideal node position location of the CS is dependent on PV penetration.

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Section: Introductionmentioning

confidence: 99%