Development of Smart Charging Scheduling and Power Management Strategy of a PV-ESS based Scalable EV Charging Station

Shahid Jaman; Boud Verbrugge; Assel Zhaksylyk; Thomas Geury; Mohamed El Baghdadi; Omar Hegazy

doi:10.1016/j.trpro.2023.11.583

Development of Smart Charging Scheduling and Power Management Strategy of a PV-ESS based Scalable EV Charging Station

Shahid Jaman, Boud Verbrugge, Assel Zhaksylyk, Thomas Geury, Mohamed El Baghdadi, Omar Hegazy

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Abstract

This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station's control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment.

Original language	English
Pages (from-to)	1240-1247
Number of pages	8
Journal	Transportation Research Procedia
Volume	72
Issue number	2023
DOIs	https://doi.org/10.1016/j.trpro.2023.11.583
Publication status	Published - 2023
Event	TRA - Transport Research Arena Conference Lisbon 2022 - Lisbon Congress Center, Lisbon, Portugal Duration: 14 Nov 2022 → 17 Nov 2022 https://traconference.eu/

Bibliographical note

Funding Information:
This work was supported by the Horizon 2020 Programme of the European Commission under grant agreement no. 875131 (eCharge4Driver project). We, as authors, also acknowledge Flanders Make for the support to our research group.

Publisher Copyright:
© 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Keywords

electric vehicle (EV)
power management
smart charging scheduling
modular
scalable
PV
ESS

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10.1016/j.trpro.2023.11.583

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title = "Development of Smart Charging Scheduling and Power Management Strategy of a PV-ESS based Scalable EV Charging Station",

abstract = "This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station's control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment. ",

keywords = "electric vehicle (EV), power management, smart charging scheduling, modular, scalable, PV, ESS",

author = "Shahid Jaman and Boud Verbrugge and Assel Zhaksylyk and Thomas Geury and {El Baghdadi}, Mohamed and Omar Hegazy",

note = "Funding Information: This work was supported by the Horizon 2020 Programme of the European Commission under grant agreement no. 875131 (eCharge4Driver project). We, as authors, also acknowledge Flanders Make for the support to our research group. Publisher Copyright: {\textcopyright} 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0); TRA - Transport Research Arena Conference Lisbon 2022, TRA Lisbon 2022 ; Conference date: 14-11-2022 Through 17-11-2022",

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AU - El Baghdadi, Mohamed

AU - Hegazy, Omar

N1 - Funding Information: This work was supported by the Horizon 2020 Programme of the European Commission under grant agreement no. 875131 (eCharge4Driver project). We, as authors, also acknowledge Flanders Make for the support to our research group. Publisher Copyright: © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

PY - 2023

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N2 - This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station's control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment.

AB - This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station's control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment.

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KW - smart charging scheduling

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KW - scalable

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ER -

Development of Smart Charging Scheduling and Power Management Strategy of a PV-ESS based Scalable EV Charging Station

Abstract

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Keywords

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