Advanced Energy Management: Digitalization and AI for the Internet of Energy presents the latest advances in the fields of distributed renewable systems, advanced controls, and energy management of nonlinear energy behaviours. The book addresses the problems of energy resilience under extreme climate and extreme events and presents new applications for energy-efficient, low-carbon and energy-reliable cities. The book explains how energy management is used in multi-energy systems for improved power dispatch, fast response, dynamic ageing, techno-economic performance. The introduction provides a comprehensive overview of artificial intelligence applications for renewable energy systems. The subsequent sections delve into various aspects, such as the interconnection between climate change and multi-energy systems, the role of big data and digitalization in sustainable energy supply, the integration of renewable energy sources, and the application of machine learning in power forecasting, demand predictions, and energy storage. Following this, the book explains demand-side management and grid-response controls in integrated energy management systems (IEMSs), and energy management systems (EMSs) in integrated energy systems and power grid with artificial intelligence. Dedicated chapters review peer-to-peer and blockchain-based energy sharing and trading, dynamic pricing and decision making in distributed energy markets, as well as city-scale energy resilience and robustness with distributed energy systems. Finally, the ethical, regulatory, and policy considerations of applying artificial intelligence in energy systems and energy management are discussed, and detailed Sustainability and Environmental Impact Analyses are presented. Advanced Energy Management: Digitalization and AI for the Internet of Energy is an invaluable reference for students, researchers, and industry professionals seeking advanced energy management strategies, and will be of interest to anyone involved in carbon neutrality solutions.
Machine Learning and Data Analysis for Energy Efficiency in Buildings: Intelligent Operation, Maintenance, and Optimization of Building Energy Systems introduces data basics, from selecting and evaluating data to the identification and repair of abnormalities. Other sections cover data mining applied to energy forecasting, including long- and short-term predictions, the introduction of occupant-focused behavior analysis, and current methods for supply and demand applications. Case studies are included in each part to assist in evaluation and implementation of these techniques across building energy systems.Working from the fundamentals of big data analysis to a complete method for building energy assessment, flexibility, and management, this book provides students, researchers, and professionals with an essential, cutting-edge resource on this important technology.
Intelligent Control in Smart Energy Systems provides a clear and practical guide to the implementation of Artificial Intelligent (AI) techniques in modern, sustainable energy systems. Building from essential theory to advanced application processes, this book outlines the essential challenge of control for renewable and distributed energy sources and applies a range of AI solutions from deep learning, data-driven decision-making, advanced control, and optimization algorithms for smart grids. Case studies and latest results cover control across design, development, and operation of smart energy systems, touching on control in generation, distribution, and supply.Catering to newly interdisciplinary researchers as well as those with a basic understanding of AI technologies, this book supports higher-stage undergraduates, graduate students, researchers, and system engineers in implementing best practice control techniques for a sustainable energy grid.
Optimal Operation and Resilience Enhancement of Integrated Power and Transport Systems is a practical guidebook that builds your skills from fundamental principles to advanced applications, using actionable tools. This book supports a solid foundation in the principles of integrated power and transport, breaking down basic system structures, the fundamentals of key techniques such as game theory and variational inequality, and their function in optimization and resilience. Part II ensures the reader has a clear understanding of the design of such systems and key considerations from essential needs to the challenges of expansion, while parts III and IV outline the opportunities offered by cooperative and non-cooperative game theory. Special challenges are covered in part V, focusing on the major disruptions of adverse weather events and unpredictable demand. Providing a broad range of replicable and amendable methods, Optimal Operation and Resilience Enhancement of Integrated Power and Transport Systems supports readers in taking practical steps to improve resilience, sustainability, and responsive in integrated transport and energy systems.
Development of Electric Vehicles in Smart Grid Concepts presents a guide to the design, development, and deployment of electric vehicles in smart grids. The book examines the current technological progression of power electronic converters for smart grid operation and EV technology as well as providing the international standards, policies, and market needs to ensure readers understand the nuanced requirements of the grid. The book begins by introducing EVs, encompassing their historical evolution, current status, and potential advancements. It delves into the architecture, components, working modes, and technological challenges within EVs.There is a dedicated chapter on international standards, governmental policies, and codes for implementation, followed by the integration of EVs into smart grids, discussing infrastructure requirements, impacts, and integration modes (V2G, G2V, V2B, and V2H). Technical aspects, modeling, and optimization methods for EV scheduling are explored alongside battery modeling, degradation, charging standards, SOC estimation, and battery management systems. Additionally, the book examines EV interaction with smart grids, renewable energy sources, energy storage systems, global market surveys, and future trends.
Reliable Non-Parametric Techniques for Energy System Operation and Control: Fundamentals and Applications of Constraint Learning and Safe Reinforcement Learning Methods offers a comprehensive guide to cutting-edge smart methods in energy system operation and control. This book begins by covering fundamentals, applications in deterministic and uncertain environments, accuracy in imbalanced datasets, and overcoming measurement limitations. It also delves into mathematical insights and computationally-efficient implementations. Part II addresses energy system control using safe reinforcement learning, exploring training-efficient intrinsic-motivated reinforcement learning, physical layer-based control, barrier function-based control, and CVaR-based control for systems without hard operation constraints. Designed for graduate students, researchers, and engineers, Reliable Non-Parametric Techniques for Energy System Operation and Control stands out for its practical approach to advanced methods in energy system control, enabling sustainable developments in real-world conditions.
Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource.
Microgrid Technology and Microgrid Cluster Development is a comprehensive guide to microgrid systems fundamentals, optimization, control, protection, and energy management.The book explains microgrid architectures that might be combined to create a cluster of microgrids. This is a valuable resource for all those looking to gain a complete understanding of current microgrid and cluster technology, including students, researchers, faculty, R&D professionals, engineers, and other industry personnel with an interest in grid integration, power systems, and renewable energy.The microgrid is first defined as a standalone entity with potential interconnections with external grids. Then, the layout, line technology, and interface technology of potential microgrid cluster topologies are designed, with comparison and analysis of the various microgrid and cluster designs in terms of price, scalability, security, dependability, stability, communications, and business models. Key aspects are covered in detail, including optimization algorithms and the role of machine learning and artificial neural networks, control and protection techniques, and energy management and storage.
‘Switchgear Design, Operation, and Maintenance using Industry Standards: Protective Mechanisms, Sensing Technology, and Communication Standards’ is a practical handbook from both industry experts and academics covering the latest developments in switchgear.This book breaks down cutting-edge practical techniques according to the hierarchy of switchgear operations, with an emphasis on critical technologies for automation in the energy transition. Following a helpful refresher on switchgear fundamentals, Part I examines essential safety considerations from fault identification and resolution to DC-type circuit breakers and other protective mechanisms. Part II sets out operating principles and testing procedures for reliable smart substations, including communication protocols, validation, and cyber-security. Finally, Part III considers essential operational maintenance such as circuit-breaker maintenance, and the critical function of high-voltage DC switchgear for the energy transition.An up-to-date helping hand for the transfer from university programs to industry, ‘Switchgear Design, Operation, and Maintenance using Industry Standards’ will allow professionals to design, operate, and maintain the smart, automated substations the energy transition needs.
Grid-Forming Converters: Principles, Control, and Applications in Modern Power Systems is a pioneering guidebook to this state-of-the-art technology and its potential in enabling more-electronics grids and deep renewable integration for the energy systems of the future. Beginning with a clear explanation of the challenges presented for the standard synchronous generator or grid-tied converters by fossil-fuel phase-out and renewable integration, this book goes on to explain the fundamental concepts of grid-forming converters.Having established a solid foundational understanding the reader will learn practical techniques for implementation including design, control, analysis, and optimization. Finally, readers tackle case studies and example applications from energy storage to electric vehicles. From several of the foremost experts and educators in energy systems and power electronics, Grid-Forming Converters is an essential tool for students, professors and engineers working to make renewable-based grids a reality.