Artificial Intelligence for Renewable Energy systems

by Ashutosh Kumar Dubey (Editor), Sushil Narang (Editor), Abhishek Kumar PhD (Editor), Vicente García-Díaz (Editor), Arun Lal Srivastav (Editor)

Overview

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.

- Includes real-time applications that illustrates artificial intelligence and machine learning for various renewable systems

- Features a templated approach that can be used to explore results, with scientific implications followed by detailed case studies

- Covers computational capabilities and varieties for renewable system design

Product Details

ISBN-13:	9780323906616
Publisher:	Woodhead Publishing, Limited
Publication date:	08/01/2022
Series:	Woodhead Publishing Series in Energy
Sold by:	Barnes & Noble
Format:	eBook
Pages:	406
File size:	30 MB
Note:	This product may take a few minutes to download.

About the Author

Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. He is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidadde Castilla-La Mancha, Ciudad Real, Spain.

Dr. Sushil Kumar Narang is Dean and an Associate Professor in the Department of Computer Science & Engineering at Chitkara University, Rajpura, Punjab since 2019. From 2006-2019, He was head of IT department at SAS Institute of IT & Research, Mohali, Punjab. From 1996-2006 he was Assistant Professor at Department of Computer Science & Applications, MLN College, Yamuna agar, Haryana. He Completed his Ph.D. at Panjab University, Chandigarh. His Research on “Feature Extraction and Neural Network Classifiers for Optical Character Recognition for Good quality handwritten Gurmukhi and Devnagari Characters” focused on various image processing, machine as well as deep learning algorithms. His research interests lie in the area of programming languages, ranging from theory to design to implementation, Image Processing, Data Analytics and Machine Learning. He has collaborated actively with researchers in several other disciplines of computer science, particularly Machine Learning on real world use cases.

Dr Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science & Engineering at Chandigarh University, Punjab. He holds a PhD in Computer Science from the University of Madras and completed postdoctoral research at the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Spain. He brings extensive expertise in data science and AI-driven analytical modelling. He has published impactful research in reputed journals such as Expert Systems with Applications, Archives of Computational Methods in Engineering, and Scientific Reports, and has published books such as Computer Vision and Machine Intelligence for Renewable Energy Systems (Elsevier) and Quantum Protocols in Blockchain Security (Springer). His research areas are artificial intelligence, renewable energy, machine learning, and image processing.

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.

Dr. Arun Lal Srivastav is an Associate Professor in the Department of Applied Sciences at Chitkara University, Himachal Pradesh, India.

Table of Contents

1. Current State of energy systems2. Artificial Intelligence and Machine Learning implications to energy systems3. Weather forecasting using Artificial Intelligence4. Intelligent Energy storage5. Modelling and Simulation of Power Electronic Circuits6. Control methods in Renewable energy systems7. Role of Artificial Intelligence in Power Quality Management and Stability Analysis 8. Integration of microgrids9. Rooftop photovoltaic systems 10. Biomass and biogas 11. Renewable energy systems and technologies education12. Evolutionary Intelligence in Renewable energy13. Smart Energetic Management 14. RnE: Renewable Energetic Systems15. Energy efficient lighting systems16. Scope of Artificial Intelligence based solar energy system17. Role of Artificial Intelligence in environmental sustainability18. Integration of Artificial Intelligence with biomethanation19. Hybrid renewable energy system and Artificial Intelligence20. Renewable energy and sustainable developments

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From the Publisher

A comprehensive reference on the advancing role of artificial intelligence in a variety of renewable energy systems