This book provides a clear explanation of how to apply artificial intelligence (AI) to solve the challenges in solar photovoltaic technology. It introduces readers to new AI-based approaches and technologies that help manage and operate solar photovoltaic systems effectively. It also motivates readers to find new AI-based solutions for these challenges by providing a comprehensive collection of findings on AI techniques. It covers important topics including solar irradiance variability, solar power forecasting, solar irradiance forecasting, maximum power point tracking, hybrid algorithms, swarm optimization, evolutionary optimization, sensor-based sun- tracking systems, single-axis and dual-axis sun-tracking systems, smart metering, frequency regulation using AI, emerging multilevel inverter topologies, and voltage and reactive power control using AI. This book is useful for senior undergraduate students, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and renewable energy.

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. - Includes intelligent methods in real-time using reconfigurable circuits FPGAs, DSPs and MCs - Discusses the newest trends in AI forecasting, optimization and control applications - Features MATLAB and Simulink examples highlighted throughout

The present book focuses on recent advances methods and applications in photovoltaic (PV) systems. The book is divided into two parts: the first part deals with some theoretical, simulation and experiments on solar cells, including efficiency improvement, new materials and behavior performances. While the second part of the book devoted mainly on the application of advanced methods in PV systems, including advanced control, FPGA implementation, output power forecasting based artificial intelligence technique (AI), high PV penetration, reconfigurable PV architectures and fault detection and diagnosis based AI. The authors of the book trying to show to readers more details about some theoretical methods and applications in solar cells and PV systems (eg. advanced algorithms for control, optimization, power forecasting, monitoring and fault diagnosis methods). The applications are mainly carried out in different laboratories and location around the world as projects (Algeria, KSA, Turkey, Morocco, Italy and France). The book will be addressed to scientists, academics, researchers and PhD students working in this topic. The book will help readers to understand some applications including control, forecasting, monitoring, fault diagnosis of photovoltaic plants, as well as in solar cells such as behavior performances and efficiency improvement. It could be also be used as a reference and help industry sectors interested by prototype development.

PHOTOVOLTAIC SYSTEMS TECHNOLOGY Discover comprehensive insights into the latest advancements in solar PV technology, including power electronics, maximum power point tracking schemes, and forecasting techniques, with a focus on improving the performance of PV systems. A huge number of research articles and books have been published in the last two decades, covering different issues of PV efficiency, circuits, and systems for power processing and their related control. Books that have been published cover one or more topics but altogether fail to give a complete picture of the different aspects of PV systems. Photovoltaic Systems Technology aims to close the gap by providing a comprehensive review of techniques/practices that are dedicated to improving the performance of PV systems. The book is divided into three parts: the first part is dedicated to advancements in power electronic converters for PV systems; tools and techniques for maximum power point tracking of PV systems will be covered in the second part of the book; and the third part covers advancements in techniques for solar PV forecasting. The overall focus of the book is to highlight the advancements in modeling, design, performance under faulty conditions, forecasting, and application of solar photovoltaic (PV) systems using metaheuristic, evolutionary computation, machine learning, and AI approaches. It is intended for researchers and engineers aspiring to learn about the latest advancements in solar PV technology with emphasis on power electronics involved, maximum power point tracking (MPPT) schemes, and forecasting techniques.

The book is concerned with the use of Artificial Intelligence in the discovery, production and application of new engineering materials. Topics covered include nano-robots. data mining, solar energy systems, materials genomics, polymer manufacturing, and energy conversion issues. Keywords: Artificial Intelligence, Mathematical Models, Machine Learning, Artificial Neural Networks, Bayesian Analysis, Vector Machines, Heuristics, Crystal Structure, Component Prediction, Process Optimization, Density Functional Theory, Monitoring, Classification, Nano-Robots, Data Mining, Solar Photovoltaics, Renewable Energy Systems, Alternative Energy Sources, Material Genomics, Polymer Manufacturing, Energy Conversion.

This book discusses control and optimization techniques in the broadest sense, covering new theoretical results and the applications of newly developed methods for PV systems. Going beyond classical control techniques, it promotes the use of more efficient control and optimization strategies based on linearized models and purely continuous (or discrete) models. These new strategies not only enhance the performance of the PV systems, but also decrease the cost per kilowatt-hour generated.

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY AND CLIMATE CHANGE Written and edited by a global team of experts in the field, this groundbreaking new volume presents the concepts and fundamentals of using artificial intelligence in renewable energy and climate change, while also covering the practical applications that can be utilized across multiple disciplines and industries, for the engineer, the student, and other professionals and scientists. Renewable energy and climate change are two of the most important and difficult issues facing the world today. The state of the art in these areas is changing rapidly, with new techniques and theories coming online seemingly every day. It is important for scientists, engineers, and other professionals working in these areas to stay abreast of developments, advances, and practical applications, and this volume is an outstanding reference and tool for this purpose. The paradigm in renewable energy and climate change shifts constantly. In today’s international and competitive environment, lean and green practices are important determinants to increase performance. Corresponding production philosophies and techniques help companies diminish lead times and costs of manufacturing, improve delivery on time and quality, and at the same time become more ecological by reducing material use and waste, and by recycling and reusing. Those lean and green activities enhance productivity, lower carbon footprint and improve consumer satisfaction, which in reverse makes firms competitive and sustainable. This practical, new groundbreaking volume: Features coverage on a wide range of topics such as classical and nature-inspired optimization and optimal control, hybrid and stochastic systems Is ideally designed for engineers, scientists, industrialist, academicians, researchers, computer and information technologists, sustainable developers, managers, environmentalists, government leaders, research officers, policy makers, business leaders and students Is useful as a practical tool for practitioners in the fields of sustainable and renewable energy sustainability Includes wide coverage of how artificial intelligence can be used to impact the struggle against global warming and climate change

CLEAN and RENEWABLE ENERGY PRODUCTION According to the World Renewable Energy Council (WREC), by the year 2100, the world’s population will increase to 12 billion and the worldwide energy demand will increase steeply to about five times the present scenario. Researchers are striving to find alternative forms of energy, and this quest is strongly forced by the increasing worry over climate change and planetary heating. Among the diverse varieties of alternative energy sources, biomass has the singular advantage of being carbon neutral. The carbon that is discharged to the atmosphere during its exercise is read back during the utilization of biomass resources for energy output. Currently, biomass provides approximately 13% of the world’s primary energy supply and more than 75% of global renewable energy. Indeed, it is estimated that bioenergy could contribute 25–33% of the global energy supply by 2050. Continued adoption of biomass will require efficient conversion rates and avoidance of competition with food and fibers. This book focuses on the recent practices in clean energy and renewable energy. The contributors highlight how newer technologies are reducing the dependency on non-renewable resources, benefiting the researchers who are working in the area of clean and renewable energy production. This new volume will also benefit mechanical engineers, electrical engineers, and bioengineers as they will be updated with the recent work progressing all over the globe. It will benefit the professionals working in the renewable energy sector such as solar, wind, hydrothermal, hydrogen, and bioenergy, including professors, research scholars, industry professionals, and students working in this field.

This proceedings book emphasizes adopting artificial intelligence-based and sustainable energy efficiency integrated with clear objectives, to involve researchers, students, and specialists in their development and implementation adequately in achieving objectives. The integration of artificial intelligence into renewable energetic systems would allow the rapid development of a knowledge-based economy suitable to the energy transition, while fully integrating the renewables into the global economy. This is how artificial intelligence has hand in by conceptualizing this transition and above all by saving time. The knowledge economy is valuated within the smart cities, which are fast becoming the favorite places where the energy transition will take place efficiently and intelligently by implementing integrated approaches to energy saving and energy supply and integrated urban approaches that go beyond individual interventions in buildings or transport modes using information and communication technologies.