Handbook of Artificial Intelligence Techniques in Photovoltaic Systems

Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting and Fault Diagnosis provides readers with a comprehensive and detailed overview of the role of artificial intelligence in PV systems. Covering up-to-date research and methods on how, when and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase PV system efficiency. Sections cover problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and more.Supported by the use of MATLAB and Simulink examples, this comprehensive illustration of AI-techniques and their applications in photovoltaic systems will provide valuable guidance for scientists and researchers working in this area.

Autorentext

Adel Mellit is a Professor at the Faculty of Sciences and Technology, University of Jijel, Algeria, and a Senior Associate Member at the International Centre of Theoretical Physics (ICTP), Trieste, Italy. He was previously the Director of the Renewable Energy Laboratory at University of Jijel. Prof. Mellit's research focuses on the application of AI techniques, including deep learning and TinyML, in solar photovoltaic systems. He has authored or co-authored over 200 papers in international peer reviewed journals and numerous papers in conference proceedings, and has acted as editor of various conference proceedings. He is an Editor of the IEEE Journal of Photovoltaics, Subject Editor of the Energy journal (Elsevier) and an editorial board member of the Renewable Energy journal (Elsevier). He co-authored the Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting, and Fault Diagnosis, published by Elsevier under the Academic Press imprint in 2022.****

Professor Soteris Kalogirou obtained his PhD and DSc from the University of Glamorgan, UK. For more than 30 years, he has been actively involved in research of solar energy and in flat plate and concentrating collectors, solar water heating, solar steam generating systems, desalination, photovoltaics and absorption cooling in particular. He has many books and book contributions and has published large number papers in international scientific journals and refereed conference proceedings. He is Editor-in-Chief of Renewable Energy and Deputy Editor-in-Chief of Energy, as well as Editorial Board Member of another eleven journals. He is the author of the book Solar Energy Engineering: Processes and Systems and Thermal Solar Desalination, both published by Academic Press of Elsevier. He has been a member of World Renewable Energy Network (WREN), American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE), Institute of Refrigeration (IoR) and International Solar Energy Society (ISES).

Klappentext
"Handbook of artificial intelligence techniques in photovoltaic systems provides readers with a comprehensive and detailed overview of the role of artificial intelligence (AI) in PV systems. Covering up-to-date research and methods of how, when, and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase the efficiency of PV systems. Each chapter solves specific problem and can stand independently; this detailed book contains problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and real-time implementation of designed intelligent models (into FPGAs, DSPs, or MCs) and smart monitoring systems."--Back cover.

Inhalt

1. Solar radiation
   
   2. Photovoltaic systems
   3. Artificial intelligence techniques
   4. Modelling and forecasting of solar radiation
   5. Sizing and optimization of photovoltaic systems
   6. Tracking the maximum power point in photovoltaic systems
   7. Control of photovoltaic systems
   8. Output power forecasting
   9. Fault detection and diagnosis techniques for photovoltaic systems
   10. Advanced or smart monitoring systems
   11. AI-technique based hardware implementation in photovoltaic systems