The scientific literature is paying particular attention to Ultra-Fast Charging Stations (UFCSs) that can make charging times of Electric Vehicles (EVs) comparable with the refuelling time of internal combustion engine vehicles. In this context, scheduling charging algorithms to manage the available resources deserve significant attention. This paper proposes an online scheduling algorithm for UFCSs equipped with Battery Energy Storage Systems. The charging profile is obtained by considering the power and energetic constraints related to both infrastructure and EVs. The constraints are assessed according to the efficiency of the infrastructure, for which a power losses estimation approach was proposed and then detailed for the UFCS realized at our department. Even, the dependence of the maximum EV charging rate on the State of Charge (SoC) is considered. These aspects are usually neglected. Thus, starting from the measurements of the maximum charging rate for two commercial EVs, numerical simulations were performed using the proposed algorithm according to two different scheduling policies, i.e., the not-preemptive ‘First Come Best Served’ and the preemptive ‘Round Robin SoC’. The numerical results highlight the difference between the two policies regarding the allocation of resources among vehicles and how the SoC of the BESS affects the overall charging profiles.

A model-based EVs charging scheduling for a multi-slot Ultra-Fast Charging Station / Attaianese, C.; Di Pasquale, A.; Franzese, P.; Iannuzzi, D.; Pagano, M.; Ribera, M.. - In: ELECTRIC POWER SYSTEMS RESEARCH. - ISSN 0378-7796. - 216:(2023), p. 109009. [10.1016/j.epsr.2022.109009]

A model-based EVs charging scheduling for a multi-slot Ultra-Fast Charging Station

Attaianese C.;Di Pasquale A.
;
Iannuzzi D.;Pagano M.;
2023

Abstract

The scientific literature is paying particular attention to Ultra-Fast Charging Stations (UFCSs) that can make charging times of Electric Vehicles (EVs) comparable with the refuelling time of internal combustion engine vehicles. In this context, scheduling charging algorithms to manage the available resources deserve significant attention. This paper proposes an online scheduling algorithm for UFCSs equipped with Battery Energy Storage Systems. The charging profile is obtained by considering the power and energetic constraints related to both infrastructure and EVs. The constraints are assessed according to the efficiency of the infrastructure, for which a power losses estimation approach was proposed and then detailed for the UFCS realized at our department. Even, the dependence of the maximum EV charging rate on the State of Charge (SoC) is considered. These aspects are usually neglected. Thus, starting from the measurements of the maximum charging rate for two commercial EVs, numerical simulations were performed using the proposed algorithm according to two different scheduling policies, i.e., the not-preemptive ‘First Come Best Served’ and the preemptive ‘Round Robin SoC’. The numerical results highlight the difference between the two policies regarding the allocation of resources among vehicles and how the SoC of the BESS affects the overall charging profiles.
2023
A model-based EVs charging scheduling for a multi-slot Ultra-Fast Charging Station / Attaianese, C.; Di Pasquale, A.; Franzese, P.; Iannuzzi, D.; Pagano, M.; Ribera, M.. - In: ELECTRIC POWER SYSTEMS RESEARCH. - ISSN 0378-7796. - 216:(2023), p. 109009. [10.1016/j.epsr.2022.109009]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/907774
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