This book begins with an overview of fundamental technical challenges, tariff mechanisms, and successful implementation examples for renewable-to-vehicle smart charging. Subsequent chapters detail cutting-edge machine learning and Internet-of-Things techniques for load-forecasting and charging resilience, before guiding readers through planning considerations including energy trading methods, fuel-cell vehicles, charging points size and location, and uncertainty modeling.

Combining a step-by-step grounding in key challenges and opportunities with practical case studies in the latest ML and AI technologies, Renewable-to-Vehicle Smart Charging: Planning, Modeling, and Load Forecasting for Grid Integration will support students, researchers, and engineers in integrating electric vehicle charging to the renewable-based grids of the future.