Vehicle-to-Grid (V2G) Systems in Smart Grids: A Review and Case Study on AI-Based Energy Management and Grid Stability

Abstract

Electric vehicles (EVs) are considered as one the most important part and parcel of future smart energy systems due to the smart electrification of transportation, and Vehicle-to-Grid (V2G) technology that leads to a viable way in improving grid flexibility, control peak loads and integrate renewable energy sources. The focus majorly on bidirectional power- electronic topologies, communication frameworks, control techniques, and AI-enabled optimization for uncertainty management and predictive operation helps to evaluate the current level of V2G research. The research addresses key deployment obstacles, such as worries about battery deterioration, immature infrastructure, unclear business models, cybersecurity vulnerabilities, and new power- quality issues including harmonics and supraharmonics, through a thorough synthesis of previous studies. A concentrated case study of India's electric bus (E-bus) transition highlights depot-level medium-voltage V2G (MV2G) as a currently underutilized system-level asset and demonstrates how fragmented planning and unidirectional grid readiness increase operational stress. Studies indicate that intelligent energy management, battery-health-aware operation, secure authentication frameworks, standardized communication protocols, and supportive regulatory procedures must all be coordinated for V2G implementation to be successful. The research indicates that in order to achieve scalable, economically viable, cyber-secure, and power-quality- resilient smart grid ecosystems, V2G must be positioned as a proactive design component rather than a post-deployment supplement.