Aygun, Ali IhsanHasan, Md ShamimJoshi, AniketKamalasadan, Sukumar2025-10-112025-10-1120250093-99941939-9367https://doi.org/10.1109/TIA.2024.3462909https://hdl.handle.net/20.500.12684/21819This paper presents a two-stage optimal charging methodology for electric vehicles that considers grid impact, load management, and optimal charging based on pricing. The charging method is distributed based on aggregators (complying with orders such as FERC 2222). The approach considers peak loading time and optimally schedules charging so that cost savings can be integrated into customer pricing as incentives. The advantages of this proposed architecture include a) demand response and maintaining load balance, b) supporting grid stability, and c) allowing prioritized charging. It is observed that the approach has significant improvement in cost saving, valley filling, and fully providing the EV charging requirements for the customers.en10.1109/TIA.2024.3462909info:eu-repo/semantics/closedAccessElectric vehicle chargingVehicle-to-gridPrivacyPricingFluctuationsFillingJob shop schedulingElectric vehicles (EVs)smart charging algorithmADMMpeak shavingvalley fillingcharging cost minimizationArticle6119409542-s2.0-85204491398WOS:001410418500032Q1Q1