Machine Learning Applications in Renewable Energy

2025
ISBN: 978-981-97-9938-1
Verlag: Springer Nature Singapore

Buch, Englisch, 244 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 597 g

Reihe: Green Energy and Technology

This book presents the need for Renewable Energy Technologies (RET) in the context of providing a solution for the depletion of conventional resources, protecting the environment and enhancing the economic situation of a country by way of providing employment opportunities for many people may be as employees in various roles or initiating their own enterprise. The book includes statistics on energy consumption changes over the past few decades from conventional to renewable energies. The future scenario of energy in view of technological advancements and the employment status past, present and future is indicated. The need and importance of standards for the efficient operation of renewable energy systems are explained. The various modern technologies that are enabling the successful implementation of RET are presented. The role of the public and government and the various financial schemes governments provide is highlighted. A few modern applications and those under development would enhance the standard of living. The statistics and situation of the various aspects in the wake of the COVID-19 pandemic before, during and future effects are discussed, for the overall benefit of one and all. The various methods of a cost analysis of a project are indicated. Solar system components and the cost estimation of the solar power system in the present-day market status are provided. The various grid integration issues have been discussed.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Manohar, Namrata

Juang, Chia-Feng

Chaurasia, Mousmi Ajay

Mozar, Stefan

Fachgebiete

• Geowissenschaften Umweltwissenschaften Umweltwissenschaften
• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. Renewable Energy Technologies (RET) – Society   and Government Perspective.- 2. Waste-to-Energy (wte).- 3. Computation of Energy from Waste.- 4. Grid Integration of Renewable Energy System(gires).- 5. Artificial Intelligence and IOT in Renewable Energy.

Über Autor(innen)

Namratha Manohar obtained her engineering degree from Osmania University, Hyderabad, Telangana, India, and her Ph.D. in Electrical Engineering from JNTU, Hyderabad. She has 18 years of experience at the middle management level at M/s. Hindustan Cables Ltd., India, and 26 years of academic experience in engineering colleges. She is an IEEE Senior member and currently serves as an Adjunct Professor in the Department of Electrical Engineering at different colleges in Hyderabad, India.

Mousmi Ajay Chaurasia is working as a Professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation, Hyderabad. She edited three books and has five patents to her name. She has worked in South Korea and Saudi Arabia and handled various projects funded by respective governments. She has been part of several International Conferences and Workshops. Her research interests are artificial intelligence, big data, geoscience, and remote sensing.

Stefan Mozar obtained his engineering degree from the University of New South Wales in Sydney, Australia, and his MBA from the University of Technology Sydney. He is a fellow of the IEEE, and of the Institution of Engineers, Australia. He is Chartered Professional Engineer and has extensive experience in industry and academia. He has held senior leadership roles in various technology companies and has taught at a number of Australian, Asian and British Universities. His work has resulted in inventions, patents and publications.

Chia-Feng Juang is currently a Distinguished Professor in the Department of Electrical Engineering at the National Chung Hsing University, Taiwan. His current research interests include computational intelligence, intelligent control, computer vision and intelligent robots. He was IEEE Computational Intelligence Society Distinguished Lecture in 2020-2022. He is Associate Editor for several journals, including the IEEE Transactions on Fuzzy Systems and IEEE Transactions on Cybernetics.