Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Idioma: inglés
Editorial: Elsevier - Health Sciences Division, US, 2022
- Tapa blanda
- Nuevo
Librería: Rarewaves.com USA, London, London, Reino UnidoRarewaves.com USA
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Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation.…
N° de ref. del artículo LU-9780323912280
- Título
- Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
- Autor
- Sanjeevikumar Padmanaban
- Editorial
- Elsevier - Health Sciences Division, US
- Año de publicación
- 2022
- Estado
- New
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 0323912281
- ISBN 13
- 9780323912280
- Peso del artículo
- 660 gramos
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development.
As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation.
- Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment
- Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum
- Addresses the advanced field of renewable generation, from research, impact and idea development of new applications
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Acerca del autor
Dr. Krishna Kumar received his BE degree in Electronics and Communication Engineering from Govind Ballabh Pant Engineering College, Pauri Garhwal, Uttarakhand, India, MTech degree in Digital Systems from Motilal Nehru NIT, Allahabad, India, in 2006 and 2012, respectively, and PhD degree in the Department of Hydro and Renewable Energy at the Indian Institute of Technology Roorkee, India, in 2023.
He is currently working as an Assistant Engineer at UJVN Ltd. (a State Government PSU of Uttarakhand) since January 2013. Before joining UJVNL, he worked as an Assistant Professor at BTKIT, Dwarahat (a Government of Uttarakhand Institution). He has published numerous research papers in international journals and conferences, including IEEE, Elsevier, Springer, MDPI, Hindawi, and Wiley. He has also edited and written books for Taylor & Francis, Elsevier, Springer, River Press, and Wiley. His current research interests include IoT, AI, and renewable energy.
Dr. Ram Shringar Rao received his Ph.D. (Computer Science and Technology) from School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi. He has worked as an Associate Professor in the Department of Computer Science, Indira Gandhi National Tribal and is currently Associate Professor in the Department of Computer Science and Engineering of Ambedkar Institute of Advanced Communication Technologies and Research, Delhi, India. He has more than 18 years of teaching, administrative and research experience. Dr. Rao has worked administrative works in the capacities of HOO (Head of Office, AIACTR), Member Academic Council (IGNTU), Chief Warden, Coordinator University Cultural Cell, Coordinator University Computer Center, HoD of Computer Sc. and Engg., Proctor, Warden, Member of BOS and Nodal Officer of Technical Education Quality Improvement Programme (TEQIP) etc.
Dr. Omprakash Kaiwartya is an Associate Professor (Networks & Cybersecurity for CAV) and PhD (PGR) Research Coordinator at the Department of Computer Science. He is also the Research Talk/Seminar Co-ordinator of the department. He was also the Course Leader for MSc Engineering Electronics and Cybernetics & Communication (2018-2024). He teaches Embedded Systems and Group Design Projects modules in MSc and Internet/Systems Technology, and Networks and Security modules in BSc.
Dr. Omprakash is leading the industry-centered Connected and Autonomous vehicle research at Nottingham Trent, and Co-Director of the Cyber Security Research Group (CSRG) at the Department of Computer Science.Dr. M. Shamim Kaiser is currently working as a Professor at the Institute of Information Technology of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. He received his Bachelor's and Master's degrees in Applied Physics Electronics and Communication Engineering from the University of Dhaka, Bangladesh in 2002 and 2004 respectively, and the Ph. D. degree in Telecommunication Engineering from the Asian Institute of Technology (AIT) Pathumthani, Thailand, in 2010. His current research interests include Data Analytics, Machine Learning, Wireless Network & Signal processing, Cognitive Radio Network, Big data and Cyber Security, Renewable Energy. He has authored more than 100 papers in different peer-reviewed journals and conferences and his google citation is more than 1020.
Prof. Sanjeevikumar Padmanaban is a full professor of electrical power engineering in the Department of Electrical Engineering, Information Technology, and Cybernetics, at the University of South-Eastern Norway. He received his PhD in electrical engineering from the University of Bologna, Italy, in 2012. Subsequently, he held positions at VIT University (India), National Institute of Technology (India), Qatar University, Dublin Institute of Technology (Ireland), University of Johannesburg (South Africa), Aalborg University (Denmark), and Aarhus University (Denmark). Prof. Padmanaban has authored over 750 scientific papers and has been listed among the world’s top 2% of scientists (from 2019) by Stanford University. He is editor, associate editor, or editorial board member for several important refereed journals, and a Fellow of the Institution of Engineers, India, the Institution of Electronics and Telecommunication Engineers, India, and the Institution of Engineering and Technology, U.K. He received a lifetime achievement award from Marquis Who’s Who–USA 2017 for his contributions to power electronics and renewable energy research.
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