A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning
Laxmikant D. Jathar,
Keval Nikam,
Umesh V. Awasarmol,
Raviraj Gurav,
Jitendra D. Patil,
Kiran Shahapurkar,
Manzoore Elahi M. Soudagar,
T. M. Yunus Khan,
M.A. Kalam,
Anna Hnydiuk-Stefan,
Ali Etem Gürel,
Anh Tuan Hoang,
Ümit Ağbulut
Affiliations
Laxmikant D. Jathar
Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India; Corresponding author.
Keval Nikam
Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Engineering, Management and Research, Akurdi, Pune, 411044, India
Umesh V. Awasarmol
Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India
Raviraj Gurav
Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India
Jitendra D. Patil
Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India
Kiran Shahapurkar
Department of Mechanical Engineering, School of Mechanical, Chemical and Materials Engineering, Adama Science and Technology University, Adama, 1888, Ethiopia
Manzoore Elahi M. Soudagar
Department of Mechanical Engineering, Graphic Era (Deemed to Be University), Dehradun, Uttarakhand, 248002, India; Corresponding author. Faculty of Mechanical Engineering, Opole University of Technology, 45-758 Opole, Poland.
T. M. Yunus Khan
Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
M.A. Kalam
School of Civil and Environmental Engineering, FEIT, University of Technology Sydney, Sydney, NSW, 2007, Australia
Anna Hnydiuk-Stefan
Faculty of Production Engineering and Logistics, Opole University of Technology, 45-758 Opole, Poland
Ali Etem Gürel
Department of Electricity and Energy, Düzce Vocational School, Düzce University, 81010, Düzce, Turkiye
Anh Tuan Hoang
Faculty of Automotive Engineering, Dong A University, Danang, Viet Nam; Corresponding author.
Ümit Ağbulut
Department of Mechanical Engineering, Mechanical Engineering Faculty, Yildiz Technical University, İstanbul, Turkiye; Corresponding author. Department of Mechanical Engineering, Army Institute of Technology Pune, Maharashtra, 411015, India.
Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.
