Intelligent Learning Approaches for Renewable and Sustainable Energy
Elsevier - Health Sciences Division (Verlag)
978-0-443-15806-3 (ISBN)
This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence.
Josep M. Guerrero is a full professor with AAU Energy, Aalborg University, Denmark. He is the director of the Center for Research on Microgrids (CROM). He has published more than 800 journal articles in the fields of microgrids and renewable energy systems, which have been cited more than 80,000 times. His research interests focus on different microgrid aspects, including hierarchical and cooperative control, and energy management systems. Dr. Pankaj Gupta his received his BE degree in Electrical Engineering from BIT, Durg, India, ME degree in Electrical Engineering from Delhi College of Engineering, Delhi University, and his PhD degree in Electrical Engineering from NIT, Kurukshetra, India. He was conferred with the prestigious POSOCO Power System Award 2017 for outstanding PhD research work on protection issues of grid connected distributed generation by the Power System Operation Corporation Ltd., a subsidiary of Power Grid Corporation, India, in partnership with the Foundation for Innovation and Technology Transfer, IIT, Delhi. Currently, Dr. Gupta is working with Indira Gandhi Delhi Technical University for Women, Delhi, India as Assistant Professor. His research interests include power system protection, microgrid control and protection, smart grid technologies, and islanding detection techniques. Ritu Kandari received her B.Tech. Degree in Electrical and Electronics from Guru Gobind Singh Indraprastha University, India, in 2010, and M.Tech. Degree in Digital Communication from Ambedkar Institute of Advanced Communication Technologies and Research, Delhi, in 2012. She joined HMR Institute of Technology and Management, Delhi as an assistant professor in 2012. She is currently pursuing her PhD. Degree in renewable energy at the Department of Electronics and Communication Engineering, IGDTUW, Delhi. Kandari has co-edited 3 books with Elsevier and was also a guest associate editor of the special issue on electricity islands for the journal Renewable & Sustainable Energy Reviews. Dr. Alexander Micallef is a Senior Lecturer with the Department of Industrial Electrical Power Conversion at the University of Malta, Malta. He has also been a guest lecturer for the PhD course on “Power Quality and Synchronization Techniques in Microgrids at Aalborg University since 2015. Dr. Micallef received the B.Eng. (Hons.), M. Sc. in Engineering, and PhD degrees from the University of Malta (Malta) in 2006, 2009 and 2015 respectively. He has authored or co-authored more than 20 journal and conference papers on microgrids, ship electrification, zero energy buildings, and power quality. Dr. Micallef is an Associate Editor for IEEE Access and the IET Smart Grids journal. He is a Senior Member of IEEE and is a member of the IEEE Standards Association, as well as vice-chair of the IEEE Malta Section and previously Chair of the Smart Buildings and Customer Systems Subcommittee within the IEEE PES SBLCS Technical Committee.
Section I: Introduction to intelligent learning approaches for renewable and sustainable energy
1. Artificial Intelligence-based sustainability in energy
2. Machine-learning-based sustainability in energy
3. Transforming the grid: AI, ML, Renewable, Storage, EVs, and Prosumers
4. Role of intelligent techniques in large-scale integration of renewable energy
5. Variability of renewable energy generation and flexibility initiatives
Section II: Applications of intelligence learning approaches for renewable and sustainable energy
6. Intelligent learning models for renewable energy forecasting
7. Intelligent learning models for balancing supply and demand
8. Intelligent learning analysis for a flexibility energy approach towards renewable energy integration
9. Intelligent learning analysis for energy management
10. Intelligent learning approaches for demand-side controller for BIPVs integrated buildings
11. Intelligent learning approaches for single and multi-objective optimization methodology
12. Intelligent learning approaches for optimization of integrated energy systems
| Erscheinungsdatum | 05.03.2024 |
|---|---|
| Verlagsort | Philadelphia |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Gewicht | 510 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 0-443-15806-1 / 0443158061 |
| ISBN-13 | 978-0-443-15806-3 / 9780443158063 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
