Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid

Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid

Release Date: July, 2024|Copyright: © 2024 |Pages: 527
DOI: 10.4018/979-8-3693-0492-1
ISBN13: 9798369304921|ISBN13 Softcover: 9798369304938|EISBN13: 9798369304945
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Description & Coverage
Description:

Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy.

This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency.

This book is explored as a crucial recipe for modern power system processes and management. The integration of energy storage, distributed generation, demand response, and thermally activated technologies into electric distribution and transmission systems is examined in detail. The book also emphasizes the importance of smart-grid technology, artificial intelligence (AI), and advanced multi-energy systems in achieving sustainability and carbon neutrality.

This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Advanced Multi-Energy-Based Hybrid System
  • AI Software Tools and Platforms
  • AI-Based Decision-Making Process
  • Artificial Intelligence
  • Data Analytics in Generation, Transmission and Consumption
  • Electrified Transportation Infrastructure
  • Energy Cascade Conversion System
  • Energy Infrastructure with Energy-Efficient Functionalities
  • Energy Management Strategy
  • Grid-Interactive Building Infrastructure
  • Low Carbon Technology in Power Generation
  • New Equipment and Devices for Emission Reduction
  • Novel Power Generation Technology
  • Renewable Energy
  • Smart Energy
  • Smart Grid
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Editor/Author Biographies
Sunanda Hazra received the Ph.D. degree in Electrical Engineering. He is presently associated with Electrical Engineering Department of Budge Budge Institute of Technology, Kolkata,W.B, India. He has eight years of teaching experience. He has published many research papers in International Journals, Conferences, Book Records. His research interest includes load dispatch, hydro thermal scheduling, renewable energy, optimization techniques, etc. He has been awarded with Young Scientist from VD Good Technology Factory in 2021. He has reviewed few research works submitted to National/International Journals. He has attended several short-term courses/faculty development programmes. He is a member of IEI.
Sneha Sultana was born on 12th July, 1988. She received B.Tech degree in 2010 from Academy of Technology, Adisaptagram, West Bengal, India. She received M.Tech degree from Dr. B. C. Roy Engineering College, Durgapur, West Bengal, India, in 2012. Presently she is acting as Assistant professor in Electrical Engineering department, Dr. B. C. Roy Engineering College, Durgapur, West Bengal, India. Her field of research interest includes radial distribution system, optimal placement of distributed generator, combined heat and power dispatch, evolutionary algorithms.
Provas Kumar Roy obtained PhD degree in Electrical Engineering from National Institute of Technology Durgapur in 2011. He received his Master degree in Electrical Machine in 2001 from Jadavpur University. He finished his Engineering studies in Electrical Engineering from Regional Engineering College, Durgapur. Presently, he is working as a Professor in Electrical Engineering Department at Kalyani Government Engineering College, India. He was the recipient of the Outstanding Reviewer Award for International Journal of Electrical Power and Energy Systems (Elsevier) in 2018, Engineering Application of Artificial Intelligence (Elsevier) in 2017, Renewable Energy Focus (Elsevier) in 2018, Ain Shams Engineering Journal (Elsevier) in 2017. He has published more than 120 research papers. Six research scholars have obtained their Ph.D. degree under his guidance and 10 students are perusing their Ph.D. under his guidance. His research interest includes economic load dispatch, optimal power flow, FACTS, automatic generation control, radial distribution network, power system stabilizer, image processing, machine learning, evolutionary computing techniques, etc.
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