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  • Renewable Energy Integration with Electric Vehicle Technology

    Renewable Energy Integration with Electric Vehicle Technology by Salkuti, Surender Reddy; Ray, Papia;

    Series: Lecture Notes in Electrical Engineering;

      • GET 12% OFF

      • Publisher's listprice EUR 213.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        83 584 Ft (79 604 Ft + 5% VAT)
      • Discount 12% (cc. 10 030 Ft off)
      • Discounted price 73 554 Ft (70 052 Ft + 5% VAT)

    73 554 Ft

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    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Springer Nature Singapore
    • Date of Publication 30 August 2026

    • ISBN 9789819587728
    • Binding Hardback
    • No. of pages562 pages
    • Size 235x155 mm
    • Language English
    • Illustrations XIV, 562 p. 303 illus., 239 illus. in color.
    • 700

    Categories

    Long 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.

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    Table of Contents:

    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.

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