Smart Grid 3.0

This book is the first on Smart Grid 3.0.

The book presents literature reviews of recent computational and communication technologies and their application in the evolution of smart grids to Smart Grid 3.0. It offers new control solutions, architectures and energy management strategies that are based on artificial intelligence and deep learning techniques.

The book details the hardware and software implementation of fault identification or detection based on synchrophasor data and machine learning. It also discusses blockchain architectures for smart grid applications such as electric vehicles, home automation and automatic metering infrastructure.

Is the first book on the modernization of smart grids to Smart Grid 3.0. Describes the communication protocols for smart grid applications using emerging technologies like LoRa, and 5G Presents the latest techniques for microgrid management using artificial intelligence

Auteur
Bhargav Appasani has completed his Ph.D. from Birla Institute of Technology in 2018. He has over of teaching experience. He has published over 70 articles in reputed international journals and conferences. He has 2 patents filed to his credit and has published a book with Springer. He is the academic editor of Journal of Journal of Electrical and Computer Engineering (Hindawi).

Nicu BIZON received a five-year degree in electronic engineering from the University "Polytechnic" of Bucharest, Romania, in 1986, and the PhD degree in Automatic Systems and Control from the same university, in 1996. Firstly, he was in hardware design with the Dacia Renault SA, Romania. Currently, he is Professor with the University of Pitesti, Romania, being the dean of the Faculty of Electronics (2012-2017), Communication and Computers. Also, he was head of University Research Department (2004-2008) and Executive Director of the Research Centre "Modeling and simulation processes and systems" (2008-2012), being manager of four research projects in field of Green and Hydrogen Energy, and team's member in other ten projects in the same research field. He is editor of seven books and author of five books in field of Green Energy, Hybrid Power Sources and Power Converters. His current research interests include the broad area of nonlinear systems, on both dynamics and control applied in the Green Energy field. He was authored or co-authored of several papers (over 300) in (web of knowledge (WoS) data base or other indexed data bases: WoS Hirsh index = 24) or international conferences proceedings. He has expertise in field of renewable energy, being evaluator of Research Projects for H2020 and FP7 Calls, EVAL-INCO and EACI Calls, NSRF 2007-13 (Greece), NEWF LPRO 2013-17 (Croatia), CNCSIS Ideas and ANCS PN II Calls (Romania) etc. He is general chair and proceedings' Editor of the "Electronics, Computers and Artificial Intelligence - ECAI" Conference, Editor-in-Chief of Journal of Electrical Engineering, Electronics, Control and Computer Science - JEEECCS, and member of the Editorial/Technical Board of several international WoS Journals and Conferences. He is IEEE Senior member from 2016. He was chair with Management of Technical Activities for IEEE Romania Section (2012).

Texte du rabat

This book is the first on Smart Grid 3.0. The book presents literature reviews of recent computational and communication technologies and their application in the evolution of smart grids to Smart Grid 3.0. It offers new control solutions, architectures and energy management strategies that are based on artificial intelligence and deep learning techniques. The book details the hardware and software implementation of fault identification or detection based on synchrophasor data and machine learning. It also discusses blockchain architectures for smart grid applications such as electric vehicles, home automation and automatic metering infrastructure.

Contenu

Chapter 1. Smart Grid 3.0: Grid with Proactive Intelligence.- Chapter 2. Blockchain for Smart Meters, Home Automation and Electric vehicles.- Chapter 3. Engineering Applications of Crowdsourcing Concept in Active Distribution Grids.- Chapter 4. Machine Learning Based Approaches for Transmission Line Fault Detection Using Synchrophasor Measurements.- Chapter 5. Data Mining-based Approaches in the Power Quality Analysis.- Chapter 6. Emerging Communication Technologies for V2X: Standards and Protocols.- Chapter 7. Machine Learning and Deep Learning Approaches for Energy Management in Smart Grid 3.0.- Chapter 8. Big Data Analytics for Enhanced Situational Awareness in Smart Grid 3.0.- Chapter 9. Evolutionary Algorithms for Load Frequency Control in Renewable Microgrids.- Chapter 10. Smart Cities: Communication Standards, Protocols and Emerging Technologies.- Chapter 11. Internet of Things for Smart Homes and Smart Cities.- Chapter 12. Internet of Things Enabled Energy Management Systemsin Renewable Microgrids.- Index.