Artificial Intelligence for Renewable Energy systems

Erscheinungsjahr 2022
ISBN: 978-0-323-90396-7
Verlag: William Andrew Publishing

Buch, Englisch, 406 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 1000 g

Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention.

Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms.

Autoren/Hrsg.

Dubey, Ashutosh Kumar

Kumar, Abhishek

García-Díaz, Vicente

Srivastav, Arun Lal

Fachgebiete

• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Current State of energy systems
2. Artificial Intelligence and Machine Learning implications to energy systems
3. Weather forecasting using Artificial Intelligence
4. Intelligent Energy storage
5. Modelling and Simulation of Power Electronic Circuits
6. Control methods in Renewable energy systems
7. Role of Artificial Intelligence in Power Quality Management and Stability Analysis 
8. Integration of microgrids
9. Rooftop photovoltaic systems 
10. Biomass and biogas 
11. Renewable energy systems and technologies education
12. Evolutionary Intelligence in Renewable energy
13. Smart Energetic Management 
14. RnE: Renewable Energetic Systems
15. Energy efficient lighting systems
16. Scope of Artificial Intelligence based solar energy system
17. Role of Artificial Intelligence in environmental sustainability
18. Integration of Artificial Intelligence with biomethanation
19. Hybrid renewable energy system and Artificial Intelligence
20. Renewable energy and sustainable developments

Über Autor(innen)

García-Díaz, Vicente
Dr. Vicente García-Díaz is a Software Engineer and has a PhD in Computer Science. He is an Associate Professor in the Department of Computer Science at the University of Oviedo. He is also part of the editorial and advisory board of several journals and has been editor of several special issues in books and journals. He has supervised 80+ academic projects and published 80+ research papers in journals, conferences and books. His research interests include decision support systems, Domain-Specific languages and eLearning.

Dubey, Ashutosh Kumar
Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. Ashutosh is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He has more than 14 years of teaching experience. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence and Object-Oriented Programming.

Kumar, Abhishek
Dr. Abhishek Kumar is a post-doctorate fellow in computer science at Ingenium Research Group, based at Universidad De Castilla-La Mancha in Spain. He has been teaching in academia for more than 8 years, and published more than 50 articles in reputed, peer reviewed national and international journals, books, and conferences. His research area includes artificial intelligence, image processing, computer vision, data mining, and machine learning.

Srivastav, Arun Lal
Dr. Arun Lal Srivastav is working as Assistant Professor at Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India. He has obtained his PhD from the Indian Institute of Technology (BHU), Varanasi, India on the adsorption of nitrate and fluoride from water. Also, he has done post-doctoral research at National Chung Hsing University, Taiwan. He is currently involved in the teaching of Environmental Science, Environmental Engineering, Disaster Management and Design Thinking to the undergraduate engineering students. His research interests include water quality surveillance, climate change, water treatment, river ecosystem, soil health maintenance, engineering education, phytoremediation and waste management. He has published > 86 research papers in various prestigious journals (Elsevier, Springer, IWA, Taylor & Francis etc.) including some book chapters and conferences. He is also the editor of 20 books with Elsevier, Springer, NOVA and Wiley. Additionally, he is also one of the series editors of Elsevier and Nova publisher on energy sustainability and e-waste management, respectively. Further, in his credit, 12 patents have been granted by the Government of India on multidisciplinary topics. He is also working on 04 Government sponsored projects (worth ~16 million INR) on phytoremediation, adsorption, capacity building, organic farming, leachate treatment, agro-waste management etc.