Renewable Energy Integration with Electric Vehicle Technology
Description
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.
More details
Persons
Surender Reddy Salkuti has been working with Woosong University, Daejeon, Republic of Korea, as an associate professor in the Department of Global Railways since April 2014. He received a Ph.D. degree in Electrical Engineering from the Indian Institute of Technology Delhi (IITD), New Delhi, India, in 2013. He was a postdoctoral researcher at Howard University, Washington, DC, USA, from 2013 to 2014. His research interests include power system restructuring issues, smart grid development with the integration of wind and solar photovoltaic energy sources, battery storage, electric vehicles, demand response, power system analysis and optimization, artificial intelligence and soft computing techniques application in power systems, and renewable energy. He has published four edited volumes with Springer (LNEE and GREEN) and over 300 research articles in peer-reviewed international journals and conference proceedings. He served as a guest editor for various international journals.
Papia Ray received her Bachelor of Engineering (Electrical Engineering) degree from Government Engineering College, Bihar, Master of Technology (Power Systems) from National Institute of Technology, Jamshedpur, and Ph.D. degree from Indian Institute of Technology, Delhi in 2013. She has more than 23 years of teaching experience. She has more than 100 research publications in journals like IET, Elsevier, Wiley, etc. She is a senior member of IEEE, a fellow of the Institution of Engineers, and a life member of ISTE. Her research interest includes power system protection, wide area measurement systems, power quality, renewable energy, forecasting, and biomedical engineering, etc. She is presently serving as a professor in the Electrical Engineering Department of NITTTR Kolkata. She has guided 5 Ph.D.s as sole supervisor and completed one research project sponsored by DST, New Delhi.
Content
Reliability Improvement by Optimal Placement and Sizing of Renewable Energy based Distributed Generation Employing Mean Oriented Particle Swarm Optimization.- Robust Control Strategy for an Interconnected Power System with Electric Vehicle SOC Estimation.- Optimized Fifteen-Level Cascaded H-Bridge Inverter: Switch Reduction Strategies and THD Mitigation via SPWM Technique.- Fractional Complex LMS Control for DSTATCOM in Three Phase SEIG based Distributed Power Generation.- Backstepping and Adaptive Backstepping Control Strategies for Parallel DC-DC Buck Converter.- Capacitor Banks and Distributed Generation Allocation in Modern Distribution Systems using Walrus Optimization.- Optimized Deep Learning Architecture for Short-Term Wind Speed Estimation.- Optimal Energy Management in Radial Distribution System with integration of distributed Generators and Shunt Capacitors.- Design, Control and Analysis of Discrete Frequency Locked Loop for DSTATCOM with Optimized PI Gains.- Coordinated Control Strategy for Interconnected DC Microgrids.- Wind-Based Electric Vehicle Charging: A Technique for Improved Performance in Variable Wind Conditions.- Optimal Location of EV Charging Stations in a Radial Distribution Network for Loss Minimization.