Artificial Intelligence for Renewable Energy Systems

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

About the Author

Dr. Ashutosh Kumar Dubey received his PhD degree in Computer Science and Engineering from JK Lakshmipat University, Jaipur, Rajasthan, India. He is currently in the department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He is also the Senior Member of IEEE and ACM. He has more than 14 years of teaching experience. He has authored a book name Database Management Concepts. He has been associated with many international and national conferences as the Technical Program Committee member. He is also associated as the Editor/Editorial Board Member/ Reviewer of many peer-reviewed journals. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence and Object-Oriented Programming.

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 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.

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.

Arun Lal Srivastav is working as an Assistant Professor at Chitkara University, in India. He is currently involved in the teaching of Environmental Science, Environmental Engineering and Disaster Management to the undergraduate engineering students. His research interests include water treatment, river ecosystem, climate change, soil health maintenance, phytoremediation, and waste management. He has published around 50 research papers in various peer-reviewed, national and international journals, conferences, and books. He has also filed 12 patents.