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.
Er. Krishna Kumar is presently working as a Research and Development Engineer at UJVN Ltd. (A Govt. of Uttarakhand Enterprises). He has more than 13 years of experience in operation & maintenance, and design of hydropower plants. Before joining UJVNL he has also worked as Assistant Professor at BTKIT, Dwarahat (A Govt. of Uttarakhand Institution). He has completed his B.E. (Electronics and Communication Engineering) from Govind Ballabh Pant Engineering College, Pauri Garhwal (A Govt. of Uttarakhand Institution), M.Tech (Digital Systems) from Motilal Nehru NIT Allahabad (A Govt. of India Institution), and presently pursuing Ph.D. from Indian Institute of Technology, Roorkee. He has published numerous research papers in international journals and conferences including IEEE, Elsevier, and Springer. He has also edited and written books on Taylor & Francis, and Wiley which are under publication. His present research area includes 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 a Senior Lecturer and Course Leader for MSc Engineering at the School of Science & Technology, Nottingham Trent University (NTU). He was a Research Associate at the Department of Computer and Information Science at Northumbria University, UK, and involved in the gLINK, European Union project. Prior to this, he was a Post-Doctoral Fellow in the Faculty of Computing, University of Technology (UTM), Malaysia. He has authored/co-authored over 100 international Journal articles, Conference Proceedings, Book Chapters, and books. Dr. Omprakash's research focuses on IoT centric smart environment for diverse domain areas including Transport, Healthcare, and Industrial Production. His recent scientific contributions are in Internet of Connected Vehicles (IoV), E-Mobility, Electronic Vehicles Charging Management (EV), Internet of Healthcare Things (IoHT), Smart use case implementation of Sensor Networks, and Next Generation Wireless Communication Technologies (6G and Beyond). 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. Dr. Sanjeevikumar Padmanaban (Senior Member, IEEE) received his Ph.D. degree in electrical engineering from the University of Bologna, Bologna, Italy, in 2012. From 2012 to 2013, he was an Associate Professor with VIT University. In 2013, he joined the National Institute of Technology, India, as a Faculty Member. In 2014, he was invited as a Visiting Researcher with the Department of Electrical Engineering, Qatar University, Doha, Qatar, funded by the Qatar National Research Foundation (Government of Qatar). In 2014, he continued his research activities with the Dublin Institute of Technology, Dublin, Ireland. From 2016 to 2018, he served as an Associate Professor with the Department of Electrical and Electronics Engineering, University of Johannesburg, Johannesburg, South Africa. Since 2018, he has been a Faculty Member with the Department of Energy Technology, Aalborg University Esbjerg, Denmark. He is currently a fellow of the Institution of Engineers, India; the Institution of Electronics and Telecommunication Engineers, India; and the Institution of Engineering and Technology, UK. He has authored over 300 scientific articles.
Title: Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Author:
ISBN: 9780323912280
Binding:
Publisher: Elsevier - Health Sciences Division
Publication Date: 2022-03-21
Number of Pages: 416
Weight: 0.6652 kg
