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Renewable-to-Vehicle Smart Charging: Planning, Modeling, and Load Forecasting for Grid Integration - Softcover
Synopsis
Renewable-to-Vehicle Smart Charging: Planning, Modeling, and Load Forecasting for Grid Integration offering a multidisciplinary approach to integrating electric vehicle charging needs into renewable-powered grids.
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.
- Builds from foundational concepts to specific, practical methodologies
- Leverages cutting-edge technologies from machine learning and the Internet-of-Things to blockchain
- Demonstrates real-world applications through case studies and detailed calculations
"synopsis" may belong to another edition of this title.
About the Authors
Saleh Aghajan-Eshkevari is a PhD researcher in the Department of Electrical Engineering of Shahid Beheshti University, Iran. His research interests include power system optimization, integration of renewable energy resources into the power grid, electric vehicles, and smart grid.
Sasan Azad is a research associate in the Electrical Network Research Institute at Shahid Beheshti University, Iran. His main areas of interest are the security and voltage stability of power systems, smart grids, and electric vehicles
Morteza Nazari-Heris is currently an Assistant Professor of Electrical Engineering at East Carolina University, USA. Previously he was an Assistant Professor of Electrical Energy Systems at Lawrence Technological University, USA. Prof. Nazari-Heris is an expert in transportation electrification and energy systems with a focus on developing tools for the intelligent, sustainable, and resilient transportation system sector and energy sector, infrastructure systems, communities, and cities.
Miadreza Shafie-khah is the Head of Research and Innovation Division at Nowocert, Dublin, Ireland, and a visiting professor at the Royal Melbourne Institute of Technology, Australia. He is the editor-in-chief or associate editor of several prestigious journals including the IEEE Transactions on Sustainable Energy and the IEEE Transactions on Intelligent Transportation Systems. His main research interest is in demand response, decentralized electricity markets, and electric vehicles.
Hamdi Abdi is currently a full Professor with the Electrical Engineering Department of Razi University, Iran. His main research interests include power system operation and planning, smart energy systems, uncertainty modelling and management, energy hubs, energy efficiency, and demand response.
From the Back Cover
Renewable-to-Vehicle Smart Charging: Planning, Modeling, and Load Forecasting for Grid Integration offering a multidisciplinary approach to integrating electric vehicle charging needs into renewable-powered grids.
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.
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