This book provides an overview of how efficient building energy management can be done, considering the increasing importance of renewable energy integration. It also includes the grid-interactive building, their control, energy management, and optimization techniques to promote better understanding among researchers and business professionals in the utility sector and across industries. This book is written and edited by leading specialists active in concurrent developments in smart building management, renewable energy research, and application-driven R&D. The experiences and research work shared help the readers in enhancing their knowledge in the field of renewable energy, power engineering, building energy management, demand, and supply management and learn the technical analysis of the same in an insightful manner. Additionally, established and emerging applications related to applied areas like smart cities, the Internet of things, machine learning, artificial intelligence, etc., are developed and utilized to demonstrate recent innovations in smart building energy management.

This book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2020), held in Krishna Engineering College, Ghaziabad, India, during December 17-18, 2020. This book discusses key concepts, challenges, and potential solutions in connection with established and emerging topics in advanced computing, renewable energy, and network communications.

This comprehensive reference text discusses simulation with case studies and realworld applications related to energy system models, the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems. The text covers analysis and modeling of the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems. It further discusses economic aspects useful for policy makers and industrial professionals. It covers important topics, including smart grids architectures, wide-area situational awareness (WASA), energy management systems (EMS), demand response (DR), smart grid standardization exertions, virtual power plants, battery degradation modeling, optimization approaches in modeling, and smart metering infrastructure. The book: Discusses the analysis and modeling of the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems Covers issues and challenges encountered in the large-scale integration of electric vehicles, energy storage systems and renewable energy systems into future smart grid design Provides simulation with case studies and real-world applications related to energy system models, electric vehicles, and energy storage systems Discusses the integration of large renewable energy systems, with the presence of a large number of electric vehicles and storage devices/systems Discussing concepts of smart grids, together with the deployment of electric vehicles, energy storage systems and renewable energy systems, this text will be useful as a reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, renewable energy, and clean technologies. It further discusses topics, including electric grid infrastructure, architecture, interfacing, standardization, protocols, security, reliability, communication, and optimal control.

includes high-quality research work by academics and industrial experts in the field of computing. includes case studies related to Artificial Intelligence, Blockchain, Internet of Things, Multimedia Big data, Blockchain, Augmented reality, Data Science, Robotics, Cybersecurity, 3D printing, Voice Assistants and Chat bots, and future communication networks. serves as a valuable reference guide for anyone seeking knowledge about the future of computing.

This book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2020), held in Krishna Engineering College, Ghaziabad, India, during December 17-18, 2020. This book discusses key concepts, challenges, and potential solutions in connection with established and emerging topics in advanced computing, renewable energy, and network communications.

Presents analysis and modeling of renewable generation uncertainty for planning and operation, beneficial for industry professionals and researchers. Discusses the dependence modeling of multi-site renewable generations in detail. Covers probabilistic analysis, useful for data analysts. Discusses various aspects of renewable energy integration i.e. technical, economic, etc. Covers correlation factors and methodologies are validated with case studies with various standard test systems.

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.

Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning is an international contributed work with the most up-to-date fundamentals and conventional methods used in smart electrical and mechanical systems. Detailing methods and procedures for the application of ML and AI, it is supported with illustrations of the systems, process diagrams visuals of the systems and/or their components, and supportive data and results leading to the benefits and challenges of the relevant applications. The multidisciplinary theme of the book will help researchers build a synergy between electrical and mechanical engineering systems. The book guides readers on not only how to effectively solve problems but also provide high accuracy needed for successful implementation. Interdisciplinary in nature, the book caters to the needs of the electrical and mechanical engineering industry by offering details on the application of AI and ML in robotics, design and manufacturing, image processing, power system operation and forecasting with suitable examples.

This book provides an overview of how efficient building energy management can be done, considering the increasing importance of renewable energy integration. It also includes the grid-interactive building, their control, energy management, and optimization techniques to promote better understanding among researchers and business professionals in the utility sector and across industries. This book is written and edited by leading specialists active in concurrent developments in smart building management, renewable energy research, and application-driven R&D. The experiences and research work shared help the readers in enhancing their knowledge in the field of renewable energy, power engineering, building energy management, demand, and supply management and learn the technical analysis of the same in an insightful manner. Additionally, established and emerging applications related to applied areas like smart cities, the Internet of things, machine learning, artificial intelligence, etc., are developed and utilized to demonstrate recent innovations in smart building energy management.