Design and Performance Assessment of a Hybrid Energy Supply for EV Charging Facilities
Keywords:
Electric Vehicle (EV) charging, battery energy storage system (BESS), hybrid energy system (HES), peak shaving, energy management system (EMS)Abstract
A rapid shift to electrification is occurring across the entire transportation industry. Even though Electric Vehicles (EVs) greatly reduce tailpipe emissions, the large-scale implementation of EVT will create new issues for existing utility grids, particularly for peak fast-charging. When EVs are charging, there is a sudden and frequent spike in demand, which creates a greater strain on the grids, increases peak demand charges, and decreases the quality of the power supplied. This paper describes the design and operational performance evaluation of a hybrid energy supply system for EV charging stations based on a Hybrid Energy Storage System (HESS). The system under review is proposed to combine photovoltaic (PV) generation, a battery energy storage system (BESS), and the utility grid for a greater flexible and reliable power supply system. The objectives are to manage peak demand, reduce dependence on the grid, and keep the voltage within a predetermined range to avoid the low/high operational range. The proposed hybrid system is capable of reducing dependence on utility grids by approximately 40% while optimizing and maintaining a desired voltage level under extreme/high charging conditions. Therefore, the proposed system is appropriate to meet the anticipated charging demands for EV in growing urban areas.
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[1] N. Ebenezer et al., "Electromobility in the global south: An equitable transition toward road passenger transport decarbonization," 2021.
[2] P. Kumar et al., "A comprehensive review of vehicle-to-grid integration in electric vehicles: Powering the future," Energy Conversion and Management: X, vol. 25, p. 100864, 2025.
[3] R. Serrano, A. Sultana, D. Kavanaugh, and H. Wang, "Increasing electric vehicle charger availability with a mobile, self-contained charging station," Sustainability, vol. 17, no. 6, p. 2767, 2025.
[4] M. S. Mastoi et al., "A study of charging-dispatch strategies and vehicle-to-grid technologies for electric vehicles in distribution networks," Energy Reports, vol. 9, p. 1777–1806, 2023.
[5] M. M. Rana, M. Atef, M. R. Sarkar, M. Uddin, and G. M. Shafiullah, "A review on peak load shaving in microgrid—Potential benefits, challenges, and future trend," Energies, vol. 15, no. 6, p. 2278, 2022.
[6] X. Tian, B. Yuan, and P. Zheng, "Tri-objective enhanced ISODATA: A synergistic framework of cluster core optimization, inter-class divergence maximization, and adaptive threshold control for smart grid load profiling," Electric Power Systems Research, vol. 247, p. 111774, 2025.
[7] J. A. L. Vilaplana, G. Yang, and E. Ackom, "From investment to net benefits: A review of guidelines and methodologies for cost–benefit analysis in the electricity sector," Energy Research & Social Science, vol. 124, p. 104052, 2025.
[8] M. Abdelsattar, A. Mesalam, A. Fawzi, and I. Hamdan, "Optimal design and analyzing the techno-economic-environmental viability for different configurations of an autonomous hybrid power system," Electrical Engineering, vol. 106, no. 4, p. 4747–4764, 2024.
[9] A. A. Z. Diab, H. M. Sultan, I. S. Mohamed, O. N. Kuznetsov, and T. D. Do, "Application of different optimization algorithms for optimal sizing of PV/wind/diesel/battery storage stand-alone hybrid microgrid," IEEE Access, vol. 7, p. 119223–119245, 2019.
[10] Å. L. Sørensen, M. C. Westad, B. M. Delgado, and K. B. Lindberg, "Stochastic load profile generator for residential EV charging," E3S Web of Conferences, vol. 362, p. 03005, 2022.
[11] A. H. A. Elkasem, M. Khamies, M. H. Hassan, L. Nasrat, and S. Kamel, "Utilizing controlled plug-in electric vehicles to improve hybrid power grid frequency regulation considering high renewable energy penetration," Int. J. Electr. Power Energy Syst., vol. 152, p. 109251, 2023.
[12] A. H. A. Elkasem, M. Khamies, M. H. Hassan, A. M. Agwa, and S. Kamel, "Optimal design of TD-TI controller for LFC considering renewables penetration by an improved chaos game optimizer," Journal of Energy Storage, vol. 72, p. 108960, 2023.
[13] M. A. Attia, M. H. Hassan, S. Kamel, and M. Khamies, "Optimized frequency stabilization in hybrid renewable
power grids with integrated energy storage systems using a modified fuzzy-TID controller," Scientific Reports, vol. 15, no. 1, p. 20095, 2025.
[14] H. M. Hasanien and A. A. El-Fergany, "Salp swarm algorithm-based optimal load frequency control of hybrid renewable power systems with communication delay and excitation cross-coupling effect," Electric Power Systems Research, vol. 176, p. 105938, 2019.
[15] A. H. A. Elkasem, M. Khamies, M. H. Hassan, L. Nasrat, and S. Kamel, "Enhancing power grid frequency stability with an optimized TID-MRAC controller and electric vehicle integration under renewable energy penetration," Neural Computing and Applications, vol. 37, p. 19037–19061, 2025.
[16] W. Zhao, Z. Zhang, and L. Wang, "Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications," Engineering Applications of Artificial Intelligence, vol. 87, p. 103300, 2020.
[17] S. Heier, Grid Integration of Wind Energy Conversion Systems. New York, NY, USA: Wiley, 1998.
[18] W. Kempton and J. Tomić, "Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy," Journal of Power Sources, vol. 144, no. 1, p. 280–294, 2005
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