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Intelligent Paradigms for Smart Grid and Renewable Energy Systems
This book addresses and disseminates state-of-the-art research and development in the applications of intelligent techniques for smart grids and renewable energy systems. This helps the readers to grasp the extensive point of view and the essence of the recent advances in this field. The book solicits contributions from active researchers which include theory, case studies and intelligent paradigms pertaining to the smart grid and renewable energy systems. The prospective audience would be researchers, professionals, practitioners and students from academia and industry who work in this field.
Power Systems Operation with 100% Renewable Energy Sources
Power Systems Operation with 100% Renewable Energy Sources combines fundamental concepts of renewable energy integration into power systems with real-world case studies to bridge the gap between theory and implementation. The book examines the challenges and solutions for renewable energy integration into the transmission and distribution grids, and also provides information on design, analysis and operation. Starting with an introduction to renewable energy sources and bulk power systems, including policies and frameworks for grid upgradation, the book then provides forecasting, modeling and analysis techniques for renewable energy sources. Subsequent chapters discuss grid code requirements...
IoT and WSN based Smart Cities: A Machine Learning Perspective
This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning.
AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications
Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Predicting Natural Disasters With AI and Machine Learning
In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges of disasters and charts a path toward proactive solutions by applying artificial intelligence (AI) and machine learning (ML). This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four ‘R...
IoT and Analytics in Renewable Energy Systems (Volume 1)
Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems
Advances in Automation, Signal Processing, Instrumentation, and Control
This book presents the select proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (i-CASIC) 2020. The book mainly focuses on emerging technologies in electrical systems, IoT-based instrumentation, advanced industrial automation, and advanced image and signal processing. It also includes studies on the analysis, design and implementation of instrumentation systems, and high-accuracy and energy-efficient controllers. The contents of this book will be useful for beginners, researchers as well as professionals interested in instrumentation and control, and other allied fields.
Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications
Due to the complexity, and heterogeneity of the smart grid and the high volume of information to be processed, artificial intelligence techniques and computational intelligence appear to be some of the enabling technologies for its future development and success. The theme of the book is “Making pathway for the grid of future” with the emphasis on trends in Smart Grid, renewable interconnection issues, planning-operation-control and reliability of grid, real time monitoring and protection, market, distributed generation and power distribution issues, power electronics applications, computer-IT and signal processing applications, power apparatus, power engineering education and industry-institute collaboration. The primary objective of the book is to review the current state of the art of the most relevant artificial intelligence techniques applied to the different issues that arise in the smart grid development.
Planning of Hybrid Renewable Energy Systems, Electric Vehicles and Microgrid
This book focuses on various challenges, solutions, and emerging technologies in the operation, control, design, optimization, and protection of microgrids in the presence of hybrid renewable energy sources and electric vehicles. This book provides an insight into the potential applications and recent development of different types of renewable energy systems including AC/DC microgrids, RES integration issues with the grid, electric vehicle technology, etc. The book serves as an interdisciplinary platform for the audience working in the focused area to access information related to energy management, modeling, and control. It covers fundamental knowledge, design, mathematical modeling, applications, and practical issues with sufficient design problems and case studies with detailed planning aspects. This book will serve as a guide for researchers, academicians, practicing engineers, professionals, and scientists, as well as for graduate and postgraduate students working in the area of various applications of RES, Electric Vehicles, and AC/DC Microgrid.
