Advancements in Smart Energy Systems : Modeling, Simulation, and Security in Electric Vehicles and Microgrids (Studies in Infrastructure and Control)

Elsisi, Mahmoud (EDT)/ Amer, Mohammed (EDT)/ Rinanto, Noorman (EDT)

Springer Nature Switzerland AG（2026/03発売）

• 製本 Hardcover:ハードカバー版／ページ数 291 p.
• 言語 ENG
• 商品コード 9783032174611

Description

This book offers a clear overview of how digital technologies and numerical methods are transforming modern energy systems. With rising demand for sustainable solutions, industries face challenges such as optimizing energy use, improving system reliability, and enhancing the performance of electric vehicles, microgrids, and energy storage systems. This book shows how tools like numerical analysis, deep learning, machine learning, and real-time simulation are being used to address these issues. It highlights advances that strengthen grid stability, improve EV and storage performance, and protect critical infrastructure from cyber threats. Through practical examples and case studies, this book demonstrates how digital innovation is shaping a smarter, more efficient, and more secure energy future. It is a valuable resource for engineers, researchers, and professionals working to advance modern energy technologies.

Considerations for Designing an Electric Vehicle Prototype Using Numerical Analysis.- False Data Injection Attacks Modeling and Impact in Microgrids: Case Study on Smart Inverters.- Deep Learning Based Smart Inverters for False Data Injection Attack Detection.- Numerical Simulation of Lithium-Iron Phosphate Battery Cell SoC Estimation Based on Thermal Effects.- Optimal Sizing, Feasibility Analysis, and Key Issues of Grid-Connected Solar Power Plants in Distribution Networks.- CBF-FLL Control-Based Voltage Source Converter for Power Quality Improvement in Distributed Power Generation Systems.- Enhancing Algorithm Efficiency and Learning Through Non-Linear Data Structure Innovations.- Implementing a Solar Cell Tracking and Monitoring System in Rural Palestinian Areas.- Real-Time Energy Storage Management in Electric Vehicle Fleets for Optimized Grid Integration.- Optimizing Maximum Power Point Tracking (MPPT) Using Metaheuristic Approximation in Charging Condition.- Smart Grid Evolution through AI-Driven Approaches: A Technological Landscape.- Review on Recent Development of Artificial Intelligence and Machine Learning Approaches in Energy Applications.

Mahmoud Elsisi received the B.Sc., M.Sc., and Ph.D. degrees from the Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt, in 2011, 2014, and 2017, respectively. He worked as an assistant professor at the Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University. From August 2019 to July 2022, he worked as an assistant professor with the Industry 4.0 Implementation Center, Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei, Taiwan. He is currently an associate professor with the Electrical Engineering Department, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan. His research interests include studying the machine learning, deep learning, the Internet of Things (IoT), cybersecurity, model predictive control, neural networks, fuzzy logic, Kalman filter, observers, decentralized control of large scale systems, robotic control, autonomous vehicle control, renewable energy, power system dynamics.

Mohammed Amer received the B.S. degree in Mechatronics Engineering from An-Najah National University, Palestine, in 2013, and the M.A., Ph.D. in Mechanical Science from National Chiao Tung University, Taiwan, in 2016 and 2020, respectively. Dr. Amer has served as an RD prime thermal engineer at Sunonwealth Electric Machine Industry Co., Ltd., from December 2020 to February 2022. He is currently an assistant professor in the Mechanical Engineering Department, at Palestine Technical University Kadoorie, Palestine. His fields of expertise and research areas include notebook cooling module improvement, electronics cooling, liquid thermal solutions, modeling and simulation, frosting and defrosting, plastic heat exchangers (dehumidification), nanofluids and heat transfer, PV/T solar systems, jet cooling, machines, aerodynamics, and mechatronics systems. 

Noorman Rinanto received the B.Eng. and M.Eng. in electrical engineering from Sepuluh Nopember Institute of Surabaya (ITS), Surabaya, Indonesia, in 2006 and 2012, respectively. He completed the Ph.D. degree at the Department of Electrical Engineering, National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan, in 2023. He is currently an assistant professor with the Marine Electrical Engineering Department, Shipbuilding Institute of Polytechnic Surabaya, Surabaya, Indonesia. His research interests include sensor fusion, machine learning, artificial intelligence, intelligent robot and automation system, battery management system, smart control system, Industrial Internet of Things (IIoT), signal and image processing.

Chun-Lien Su received the Diploma degree in Electrical Engineering from National Kaohsiung Institute of Technology, Taiwan, the M.S. and Ph.D. degrees in Electrical Engineering from the National Sun Yat-Sen University, Taiwan, in 1992, 1997, and 2001, respectively. In 2002 and 2006, he was an assistant professor and an associate professor at the Department of Marine Engineering, National Kaohsiung Marine University, Taiwan, respectively. From 2012 to 2017, he was as a full professor where he was the director at the Energy and Control Research Center. From August 2017 to January 2018, he was a visiting professor at the Department of Energy Technology, Aalborg University, Denmark. He was the director at the Maritime Training Center, National Kaohsiung University of Science and Technology (NKUST) from February 2018 to July 2020.