Synopsis
The issue of intermittency, or variations in solar irradiance caused by weather, time of day, and geographic considerations, confronts the solar energy industry. Because of this unpredictability, precise forecasting and effective management of solar power generation are essential for a steady supply of energy. Simultaneously, artificial intelligence (AI) approaches, in particular machine learning (ML), deep learning (DL), and neural networks, have shown promise in resolving intricate, nonlinear issues across a range of areas. However, the utilization of these technologies for projecting solar irradiance and optimizing energy management is yet to be explored in depth, necessitating specific skills and methods to properly tap into their potential. AI-Driven Solutions for Solar Energy Efficiency, Irradiance Modeling, and PV Forecasting examines the relationship between solar energy and AI, with a particular emphasis on how AI-driven methods can improve solar power systems' performance, efficiency, and forecasting. It illustrates how AI-based optimization algorithms may maximize energy output and reduce losses in photovoltaic (PV) systems and solar power plants. Covering topics such as charge management, microgrids, and smart building designs, this book is an excellent resource for engineers, executives, policymakers, technologists, environmental advocates, business leaders, investors, professionals, researchers, scholars, academicians, and more.
About the Authors
Auzuir Ripardo de Alexandria is a computer scientist, electrical engineer, researcher and professor with a master's degree and doctorate in Telematics Engineering. He currently teaches in the Postgraduate Program in Telecommunications Engineering (PPGET), in the Postgraduate Program in Renewable Energies (PPGER), Northeast Education Network (RENOEN, Doctorate), Mechatronics Engineering and Technologist in Industrial Mechatronics. Furthermore, he enjoys teamwork and interdisciplinary work, having worked in recent years in the design, coordination and execution of interdisciplinary projects, having a history of projects in the areas of Biomedical Engineering and Health IT, Robotics and Computer Vision, Artificial Intelligence, among others. The main skills are: Computer Vision, Robotics, Cloud Computing, C++ and Artificial Intelligence.
Prashant Upadhyay is an Assistant Professor at, the Department of CSE, School of Engineering and Technology, Sharda University Greater Noida, Uttar Pradesh, India. He completed his Doctorate of Philosophy in Computer Science and Engineering, Gautam Buddha University. He has more than 07 years of teaching and research experience. He published several research papers in internationally reputed journals indexed in Web of Science, SCOPUS & SCIE and top-rank conferences as author or co-author. His research findings are published in Archives of Computational Methods in Engineering Springer, Computers and Electrical Engineering Elsevier, IGI Global USA, IEEE Xplore, Taylor and Francis. He served as a TPC and reviewer in Various International Conferences. He has edited 11 books with various publishers, including IGI Global, Bentham Science, and CRC Press, among others. He served as session chair in several international conferences- NGISE-2025, ICDT-2024, ICDETGT-2023, and ICDT-2023. He has authored a book for Wiley Publication- Introduction to Python, ISBN: 978-93-5746-219-8 and currently he is working on the book titled “Data Science in Business Analytics”. He has published 8 Indian patents and holds 2 grants.
Dr Antonino Galletta is an assistant professor in Computer Science (INF/01) at the University of Messina. In 2020 he received a PhD from the inter-university consortium composed of the University of Reggio Calabria (Italy) and the University of Messina (Italy). He received his B.Sc. and M.Sc. (with honours) in Computer Engineering from the University of Messina. Before starting the PhD, he worked as a senior software developer and a team leader at the University of Messina from 2013 to 2016. In 2019 he was the PI of NAME (Helsinki Noise and Air quality Monitoring systEm) a project funded by the European Pre -Commercial Procurement Project “Select for Cities” (Grant Agreement No 688196). His main research activities focus on Cloud/Edge/IoT technologies for Smart cities and eHealth including Big Data management and Blockchain. He has several international collaborations with worldwide research centers such as the University of Karlstad and of Mälardalen (Sweden), Cardiff University (UK), the Technische Universität of Wien (Austria) and the Federal University of Juiz de Fora (Brasil). Due to his contribution to the research, he has been selected among 200 top young researchers in Mathematics and Computer Science to participate at the prestigious “Heidelberg Laureate Forum” held in Heidelberg in September 2019. He has been the winner of two editions of the precious “Leonardo Innovation Award” in 2018 (First Placed) and in 2017 (Second Placed). In 2019 he was one of the winners of the FIWARE Genoa Hackathon. In 2018, in December he won the Vienna FIWARE challenge and in April, during the “International Conference on Geoinformatics and Data Analysis” (ICGDA, Prague 20-22 April), he won the “Best Presentation Award”. He is a reviewer of more than 15 respected Journals, Chair of several International Conferences and co-author of more than 50 manuscripts.
Yashaswini Sharma is an Assistant Professor at the Department of Electrical Electronics and Communication Engineering, School of Engineering and Technology, Sharda University Greater Noida, Uttar Pradesh, India. She was awarded a PhD degree from Malaviya National Institute of Technology (MNIT) Jaipur in March 2024. She has 02 years of teaching and 4.5 years of research experience. She published research papers in internationally reputed journals indexed in SCI, Web of Science, SCOPUS & SCIE. She has also presented and published research papers in top-rank conferences. She contributed as session chair, reviewer and organising committee member in ICEECT 2024. She has 1 patent granted and 2 patents published. Her research area includes Wireless communication, Cognitive Radio, spectrum sensing.
Dr. Satya Prakash Yadav (FIETE & SMIEEE) is currently the Associate Professor of the Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, U.P., India and has completed his Postdoctoral Research Fellow from Federal Institute of Education, Science and Technology of Ceará, Brazil. He has awarded his PhD degree from Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). Currently, 4 students are working for Ph.D. under his guidance. A seasoned academician having more than 18 years of experience, he has published four books (Programming in C, Programming in C++ and Blockchain and Cryptocurrency) under I.K. International Publishing House Pvt. Ltd. Including Distributed Artificial Intelligence: A Modern Approach, Published December 18, 2020 by CRC Press. He has undergone industrial training programs during which he was involved in live projects with companies in the areas of SAP, Railway Traffic Management Systems, and Visual Vehicles Counter and Classification (used in the Metro rail network design). He is an alumnus of Netaji Subhas Institute of Technology (NSIT), Delhi University. A prolific writer, Dr. Satya Prakash Yadav has published six patents and authored many research papers in web of science indexed journals. Additionally, His area of specialisation is in the areas of Image Processing, Information retrieval and Features extraction. Also, he is a Editor in Chief in Journal of Cyber Security in Computer System & Journal of Soft Computing and Computational Intelligence (MAT journals), Series Editor in DeGruyter International Publisher, Bentham Science and CRC Press, Taylor and Francis Group Publisher (U.S.A), Lead Editor in Tech Science Press (Computer Systems Science and Engineering), International Journal of Experimental Research and Review, Measurement: Sensors (Elsevier Publisher), International Journal of Advanced Technology and Engineering Exploration (IJATEE) Journal of Electrical Systems (JES), Journal of Advances in Information Technology (JAIT) and Informing Science Journal.
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