Intelligent Control in Smart Energy Systems provides a clear and practical guide to the implementation of Artificial Intelligent (AI) techniques in modern, sustainable energy systems. Building from essential theory to advanced application processes, this book outlines the essential challenge of control for renewable and distributed energy sources and applies a range of AI solutions from deep learning, data-driven decision-making, advanced control, and optimization algorithms for smart grids. Case studies and latest results cover control across design, development, and operation of smart energy systems, touching on control in generation, distribution, and supply.
Catering to newly interdisciplinary researchers as well as those with a basic understanding of AI technologies, this book supports higher-stage undergraduates, graduate students, researchers, and system engineers in implementing best practice control techniques for a sustainable energy grid.
Catering to newly interdisciplinary researchers as well as those with a basic understanding of AI technologies, this book supports higher-stage undergraduates, graduate students, researchers, and system engineers in implementing best practice control techniques for a sustainable energy grid.
Table of Contents
1. Introduction to Smart Energy Systems and Advanced Intelligent Control2. Power Electronic Components in Smart Energy Systems
3. System Architectures of Intelligent Control in Smart Energy Systems
4. Model-based Intelligent Control in Smart Energy Systems
5. Reinforcement Learning Control in Smart Energy Systems
6. Power Systems Control in Smart Energy Systems
7. Model Predictive Control in Smart Energy Systems
8. Evolutionary Algorithms in Smart Energy Systems
9. Distributed Energy Resource Management
10. Distributed Control and Decision Making
11. Implementing Intelligent Control of Smart Energy Systems
12. Sensor Networks and Data Acquisition in Smart Energy Systems
13. Fault Diagnosis and Safety of Smart Energy Systems
14. Grid Interfacing in Smart Energy Systems
15. Solid-State Relays and Solid-State Circuit Breakers for Smart Energy Systems
16. System Interoperability and Communication
17. Advanced Intelligent Control for Smart Energy Systems
18. Advanced Technologies for Intelligent Control of Smart Energy Systems
19. Applications of Intelligent Control in Smart Energy Systems
20. Conclusion and Future Directions
Authors
Satya Prakash Yadav Associate Professor, School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida, U.P., India.Satya Prakash Yadav is currently an Associate Professor in the School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida, U.P., India. He has undergone industrial training programs during which he was involved in live projects. with companies in the areas of SAP, Railway Traffic Management Systems, and Visual
Vehicles Counter and Classification (used in the Metro rail network design). He has published two patents, as well as authoring many research articles and conference papers on subjects including image processing, information retrieval, digital image processing, feature extraction, data structure, C, C++, C#, and Java.
Vinod Kumar Yadav Professor, Electrical Engineering Department, Delhi Technological University, India. Vinod Kumar Yadav is a Professor in Electrical Engineering Department, Delhi Technological University, India. His research interests include renewable energy systems, power system planning and optimization, distributed generation and smart grids. Victor Hugo Costa de Albuquerque Professor and Senior Researcher, Federal University of Ceara, Fortaleza, Graduate Program on Teleinformatics Engineering, Fortaleza/CE, Brazil. Victor Hugo C. de Albuquerque [M'17, SM'19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Cear�, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Cear�, Fortaleza/CE, Brazil.He has a Ph.D in Mechanical Engineering from the Federal University of Para�ba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Cear� (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Cear� (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic. Fadi Al-Turjman Associate Dean and Founding Director, Research Center for AI and IoT, AI and Robotics Institute, Near East University, Nicosia, Mersin 10, Turkey. Dr. Fadi Al-Turjman is the Associate Dean for Research Center for AI and IoT, AI and Robotics Institute, Near East University, Nicosia, Mersin 10, Turkey. He received his Ph.D. in Computer Science from Queen's University, Canada. Dr. Al-Turjman is a leading authority in the areas of smart/intelligent, wireless, and mobile networks. His publication history spans over 400 SCI/E publications, and more than 11,000 citations, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 40 books about cognition, security, and wireless sensor networks' deployments in smart IoT environments, which have been published by well-reputed publishers such as Taylor and Francis, Elsevier, IET, and Springer. Dr. Al-Turjman received several recognitions and best papers' awards at top international conferences, including Best Research Paper Award from Elsevier Computer Communications Journal. Dr. Al-Turjman has led a number of international symposia and workshops for flagship communication society conferences. Currently, he serves as book series editor and lead guest/associate editor for several top tier journals, including IEEE Communications Surveys and Tutorials and Elsevier Sustainable Cities and Society, in addition to organizing international conferences and symposiums on leading-edge research topics in AI and IoT.
