Intelligent and Sustainable Power and Energy Systems

1. Auflage 2025
ISBN: 978-1-041-10314-1
Verlag: CRC Press

Buch, Englisch, 328 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 623 g

“Intelligent and Sustainable Power and Energy Systems” delves into the critical advancements shaping the future of global energy. This compilation presents cutting-edge research and innovative solutions addressing the urgent need to transition towards environmentally responsible and technologically sophisticated energy infrastructures. Explore the integration of artificial intelligence, machine learning, and advanced control systems in optimising energy generation, distribution, and

consumption. Discover novel approaches to renewable energy integration, smart grid technologies, and energy storage solutions, all geared towards enhancing efficiency and minimising environmental impact. From theoretical frameworks to practical implementations, this work offers a comprehensive overview of the latest developments, providing essential insights for researchers, engineers, and policymakers striving to build a resilient and sustainable energy future. This book is a vital resource for navigating the complex challenges and opportunities in the evolving landscape of power and energy systems.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Premkumar, M.

Usha, Pasumarthi

Kumar, Sujit

Gopisetti, Manikanta

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

1. Comparative Study of Non-Isolated DC-DC Converters for Fuel Cell Electric Vehicles, 2. Secure File Storage System to Secure the Security Algorithm and Password, 3. Optimal Allocation of Distributed Generators in Distribution System with Various Load Models, 4. Power Quality Issues and Improvement Techniques, 5. Advanced Control Strategies for Distributed Generation in Microgrids: Enhancing Efficiency, Reliability and Renewable Energy Integration, 6. A Novel Nine-Level Switched Capacitor Multilevel Inverter Topology with Common Ground Configuration, 7. Optimised EV Charging Infrastructure: A Grid-Integrated Solar and Battery Storage System with Triple-Loop Control, 8. Parameter Optimisation of PID Controller Utilised for Speed Control of DC Motor with Ziegler-Nichols and Cohen-Coon Tuning Method, 9. Wireless Personal Protection for High Voltage Alert System, 10. Neuro-Oncology Reimagined: Tailored Prognosis for Brain Tumors Using Adaptive Machine Learning, 11. Automated Schizophrenia Detection and Classification (STFDL-ASDC): A Proposed Model for Self-Reported Schizophrenic Episodes, 12. Journey Toward Sustainability: Advancements in Hybrid Electric Vehicle Development, 13. Role of DC-DC Converters in Battery Management Systems, 14. Wind Power Forecasting using Machine Learning, 15. Cost Optimization of Microgrid in EV Application using PSO Algorithm, 16. Real-Time Cell Monitoring and Parameter Estimation for EV Applications, 17. Sound-Sensor-Based Emergency Vehicle Priority Detection at Urban Traffic Intersections, 18. Efficiency Enhancement of a Two-Stage Three-Phase Grid-Connected Solar-PV System Using Simplified Power Regulation Techniques, 19. Battery Management System for Electric Vehicle Using AI, 20. Real-Time Monitoring and Alert System for Earthing Integrity in Electrical Installations, 21. Photovoltaic Based Charging of 5V Smart Gadgets in Indian Household, 22. AI-Based Control System for Wireless EV Charging with Real-Time Battery Monitoring and Management, 23. A Scalable AI-Driven Framework for Sustainable Ride-Sharing and Intelligent Logistics Using Advanced Route Optimization, 24. Single-Axis Sun Tracker for PV Panels Using a Single-Slit Sun Sensor, 25. Analysis of Plant Health using Python Image Processing—An Innovative Agro Technique, 26. Alzheimer’s Care Assistant: A Machine Learning-Based Wearable Solution for Cognitive Support and Monitoring, 27. A Systematic Review of Active Balancing Strategies in Electric Vehicle Battery Systems, 28. Analysis of Electrical Discharge Plasma Based Technique on Seed Germination and Plant Growth—An Innovation Towards Agro-Sector, 29. IoT-Driven Solar-Powered Variable Speed Induction Motor System Aligned with Sustainable Development Goals, 30. AI-Based Fuel and Energy Management System (EMS) in Hybrid Electric Vehicle (HEVs): A Review, 31. AI-Based Symptom Diagnosis with Integrated HER (Electronic Health Records) using Wearable Health Devices and IoT, 32. Soft Switching Converter-based EV Fast Charging Station Deploying Sustainable Energy, 33. AI Based System for Real-Time Electric Theft Identification, 34. Novel Spatio-Temporal Hybrid Model for Rainfall Prediction in Andhra Pradesh Using USGS Satellite Data

Über Autor(innen)

Dr. M. Premkumar is working as a Professor and head of the Electrical and Electronics Engineering Department at the Dayananda Sagar College of Engineering, Bengaluru, India. He has over 17 years of teaching experience. He has published over 180 technical articles in various National/International peer-reviewed journals, such as IEEE, Elsevier, Springer, and so on, with over 4500 citations and an H-index of 37. He has published/granted twelve patents by IPR, India, and IPR, Australia. He is also an Editor/Reviewer for leading journals of different publishers, such as IEEE, IET, Wiley, Taylor & Francis, Springer, MDPI, etc. He is recognised as one of the Top 2% of Scientists Worldwide based

on the Study Conducted by Stanford University for the four consecutive years (2020, 2021, 2022, and 2023). His current research interests include power converters/inverters, renewable energy systems, smart grid and microgrids, PV parameter extraction, modern PV MPPTs, PV array faults, non-isolated/isolated dc-dc converters for renewable energy systems and electric vehicles, BMS for electric vehicles, and optimisation algorithms, including single-, multi-, and many-objectives for real-time power electronics and power systems problems.

Dr. Pasumarthi Usha received the B.Tech from E&EE in 1990, M.Tech in Power System with emphasis in High Voltage from J.N.T.U, College of Engineering Kakinada in 1992, and the Ph.D. in HVDC Power Transmission from Visvesvaraya Technical University in 2013, respectively. She works as a Professor at the Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering. Her research areas are HVDC Power systems, Microgrid, and Power Electronics.

Dr. Sujit Kumar received his PhD in Electrical Engineering from MPUAT, CTAE, Udaipur, with the collaboration of IIT Roorkee with the DST Inspire Fellowship. He also worked as SRF at IIT Roorkee during the period of his PhD. He did his M. Tech from Sharda University, Greater Noida, as a Gold Medallist, and his B.E from Birla Institute of Technology and Science, Pilani (BITS Campus) as a gold medallist. During his B.E., he received a Governor of France Scholarship for his academic excellence. He is currently posted as an Assistant Professor in the Department of Electrical and Electronics Engineering at Dayananda Sagar College of Engineering, Bengaluru, India. He receives the prestigious Gold Medal in the NPTEL training course (Fuzzy Sets, Logic and Systems & amp; Applications) and exemplifies professional development and lifelong learning excellence. He secured all India ranks in GATE 2017 and GATE 2018 as 16 and 17, respectively. His expertise includes Nanotechnology, Material Science, Sustainable Energy, and Artificial Intelligence in Power Systems.

Dr. Manikanta Gopisetti is an assistant professor at Dayananda Sagar College of Engineering, Bengaluru, India. He completed his Ph.D. in Electrical Engineering from AUUP, Amity University in 2021. He received his M. Tech. degree in Power System Engineering, from SRM University Chennai, India. He graduated from Chaitanya Engineering College, Visakhapatnam, India. He has received two best paper awards in IEEE indexed conferences. He has published many research papers in reputed journals and conference proceedings. He delivered some talks on Distributed generators, Network reconfiguration and Electric Vehicles. His research interests include Distributed Generation, Network Reconfiguration, Electric Vehicles, Evolutionary Computation, and Renewable Energy Sources.