Microgrids: Modeling, Control, and Applications presents a systematic elaboration of different types of microgrids, with a particular focus on new trends and applications. The book includes sections on AC, DC and hybrid AC/DC microgrids and reflects state-of-the-art developments, covering theory, algorithms, simulations, error and uncertainty analysis, as well as novel applications of new control techniques. Offering a valuable resource for students and researchers working on the integration of renewable energy with existing grid and control of microgrids, this book combines recent advances and ongoing research into a single informative resource. The book highlights recent findings while also analyzing modelling and control, thus making it a solid reference for researchers as well as undergraduate and postgraduate students.

Control of Standalone Microgrid looks at a practical and systematic elaboration of the architecture, design and control of standalone microgrids. It is oriented towards more advanced readers who want to enhance their knowledge in the fields of power engineering, sustainable energy, microgrids and their control. With an enriched collection of topics pertaining to the architecture and control of standalone microgrids, this book presents recent research that will bring advancements in the current power system scenario, discussing operational and technical issues due to high penetration of distributed generation units. Including executable plans for standalone microgrid systems this book enables researchers and energy executives to understand the future of energy delivery systems as well as global case studies and models to apply control techniques for standalone microgrids and protection schemes which provide a deeper level of understanding.

Advances in Smart Grid Power System: Network, Control and Security discusses real world problems, solutions, and best practices in related fields. The book includes executable plans for smart grid systems, their network communications, tactics on protecting information, and response plans for cyber incidents. Moreover, it enables researchers and energy professionals to understand the future of energy delivery systems and security. Covering fundamental theory, mathematical formulations, practical implementations, and experimental testing procedures, this book gives readers invaluable insights into the field of power systems, their quality and reliability, their impact, and their importance in cybersecurity.

Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references. This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence.