Electric Vehicle Charging

Electric vehicle (EV) charging research focuses on optimizing charging strategies to manage increasing electricity demand and ensure grid stability, while also considering user preferences and cybersecurity. Current research employs various models, including multi-agent systems, reinforcement learning (particularly deep Q-networks and actor-critic methods), and deep learning architectures like transformers and graph neural networks, to forecast charging demand, optimize pricing, and coordinate charging across networks. These advancements are crucial for enabling widespread EV adoption by mitigating grid stress, improving charging efficiency, and enhancing the user experience, impacting both the energy sector and transportation infrastructure.