A review on electric vehicle charging station operation considering market dynamics and grid interaction
Saheb Ghanbari Motlagh, Jamiu O. Oladigbolu, Li Li
Abstract
The growing adoption of Electric Vehicles (EVs) presents pressing challenges and opportunities for power systems and market dynamics. This paper comprehensively reviews state-of-the-art operational optimization techniques for EV charging, including model predictive control , reinforcement learning, and distributed approaches. The study examines strategies to address uncertainties in renewable generation , market pricing, and EV charging behavior. Advanced pricing schemes like distribution locational marginal pricing and game-based methods are explored to align profitability with system stability . The significance of bidirectional charging in reducing peak loads, supporting ancillary services, and balancing battery degradation with user satisfaction is also discussed. Finally, emerging challenges in privacy, multi-energy coupling, and regulation are presented, emphasizing research directions to enhance grid resilience, economic viability, and sustainability . This review offers valuable insights for policymakers, energy utilities, and EV stakeholders to facilitate a smooth and cost-effective transition toward an electrified and decarbonized transportation and power sector.