This book presents different aspects of renewable energy-based electric vehicle (EV) integration into the grid system. In this book, different challenges during the integration of EVs to the grid are discussed. Further, by enabling EVs to act as distributed energy storage units in a grid system, how to improve grid stability and reduce the risk of outages by providing critical support to the grid during peak demand periods and periods of renewable energy intermittency are also discussed. This book emphasizes various schemes for data privacy and cybersecurity during the integration of EVs into the grid. It also discussed how plug-in hybrid electric vehicles (PHEVs) can help reduce energy demand during peak hours and earn revenue for owners. This book presents the application of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) in the seamless integration of renewable energy-based EVs into the grid. This book leads toward cost-effective and environmentally benign utilization of a future energy system portfolio by providing a cyber-enabled sustainable pathway toward deep integration of intelligent decision-makers in the renewable energy-based EV into the grid system. This book is an effort to educate the next generation of academicians, researchers, and industry personnel with proficient analytics and improve national energy sustainability.
