A Comprehensive Review of Electric Vehicle Charging Station Integration and Its Impact on Power System Performance

Abstract

The rapid growth of Electric Vehicles (EVs) has accelerated the deployment of Electric Vehicle Charging Stations (EVCSs), making their integration into modern power systems increasingly important. While EVCSs support transportation electrification and global decarbonization goals, large-scale integration introduces technical challenges that affect power system operation, reliability, and planning. This review provides a comprehensive assessment of the impact of EVCS integration on power system performance by examining charging technologies, charging stations, charging modes, and the principal components of EVCSs. The review discusses the effects of EV charging on load demand, peak load, voltage profile, voltage stability, active and reactive power losses, transformer loading, and overall grid performance. It further evaluates mitigation strategies, including smart charging, coordinated charging, Demand Response (DR), Renewable Energy Sources (RESs), Battery Energy Storage Systems (BESSs), Vehicle-to-Grid (V2G) technology, and Artificial Intelligence (AI)-based energy management. The application of Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), and advanced optimization algorithms for charging coordination and demand forecasting is also reviewed. Finally, the paper identifies current research challenges and future directions related to charging uncertainty, renewable energy integration, cybersecurity, interoperability, and infrastructure development. The findings demonstrate that intelligent charging strategies combined with renewable energy integration, energy storage, V2G, and AI significantly improve the reliability, efficiency, resilience, and sustainability of future EV-integrated power systems.