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Review

Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration

1
The Department of Engineering, Durham University, Durham DH1 3LE, UK
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Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle Upon Tyne NE1 8SA, UK
3
Department of Engineering, Iskenderun Technical University, Hatay 31200, Turkey
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School of Engineering, Newcastle University, Newcastle Upon Tyne NE1 7RU, UK
5
School of Engineering, Istanbul University-Cerrahpasa, Istanbul 34320, Turkey
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School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
*
Authors to whom correspondence should be addressed.
Energies 2025, 18(17), 4599; https://doi.org/10.3390/en18174599
Submission received: 9 July 2025 / Revised: 11 August 2025 / Accepted: 26 August 2025 / Published: 29 August 2025

Abstract

The integration of electric vehicles (EVs) into smart grids (SGs) is reshaping both energy systems and mobility infrastructures. This review presents a comprehensive and cross-disciplinary synthesis of current technologies, methodologies, and challenges associated with EV–SG interaction. Unlike prior reviews that address these aspects in isolation, this work uniquely connects three critical pillars: (i) the evolution of energy storage technologies, including lithium-ion, second-life, and hybrid systems; (ii) optimisation and predictive control techniques using artificial intelligence (AI) for real-time energy management and vehicle-to-grid (V2G) coordination; and (iii) cybersecurity risks and post-quantum solutions required to safeguard increasingly decentralised and data-intensive grid environments. The novelty of this review lies in its integrated perspective, highlighting how emerging innovations, such as federated AI models, blockchain-secured V2G transactions, digital twin simulations, and quantum-safe cryptography, are converging to overcome existing limitations in scalability, resilience, and interoperability. Furthermore, we identify underexplored research gaps, such as standardisation of bidirectional communication protocols, regulatory inertia in V2G market participation, and the lack of unified privacy-preserving data architectures. By mapping current advancements and outlining a strategic research roadmap, this article provides a forward-looking foundation for the development of secure, flexible, and grid-responsive EV ecosystems. The findings support policymakers, engineers, and researchers in advancing the technical and regulatory landscape necessary to scale EV–SG integration within sustainable smart cities.
Keywords: electric vehicles (EVs); smart grids; vehicle-to-grid (V2G); energy storage systems (ESSs); artificial intelligence (AI); cybersecurity; digital twins (DTs); wireless charging; renewable energy integration; post-quantum cryptography electric vehicles (EVs); smart grids; vehicle-to-grid (V2G); energy storage systems (ESSs); artificial intelligence (AI); cybersecurity; digital twins (DTs); wireless charging; renewable energy integration; post-quantum cryptography

Share and Cite

MDPI and ACS Style

Cavus, M.; Ayan, H.; Bell, M.; Dissanayake, D. Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration. Energies 2025, 18, 4599. https://doi.org/10.3390/en18174599

AMA Style

Cavus M, Ayan H, Bell M, Dissanayake D. Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration. Energies. 2025; 18(17):4599. https://doi.org/10.3390/en18174599

Chicago/Turabian Style

Cavus, Muhammed, Huseyin Ayan, Margaret Bell, and Dilum Dissanayake. 2025. "Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration" Energies 18, no. 17: 4599. https://doi.org/10.3390/en18174599

APA Style

Cavus, M., Ayan, H., Bell, M., & Dissanayake, D. (2025). Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration. Energies, 18(17), 4599. https://doi.org/10.3390/en18174599

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