Building Energy Management Systems and Techniques: Principles, Methods, and Modelling presents the fundamental concepts, methodologies, modeling techniques, and design schemes of building energy management systems. Covering the latest developments and methodologies, the book brings together energy management, demand response, evolutionary computation, and fundamental programming. The book's authors explore the fundamental concepts related to building energy management systems and put them into the context of smart grids, demand response and demand side management, Internet of Things, and distributed renewable energy. Advanced topics provide the reader with an understanding of various energy management scenarios and procedures for modern buildings in an automatic and highly renewable-penetrated building environment. This includes a range of energy management techniques for building-side energy resources such as battery energy storage systems, plug-in appliances, and HVAC systems.

Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system's stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.

In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.

In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications.

Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications.

The book includes portable tool sets for many industrial applications, including:

• Forecasting machine tool wear in industrial cutting machines
• Reduction of sensors and features for industrial fault detection and isolation (FDI)
• Identification of critical resonant modes in mechatronic systems for system design of R&D
• Probabilistic small-signal stability in large-scale interconnected power systems
• Discrete event command and control for military applications

The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.

Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system's stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.

This book presents a detailed pedagogical description of the 5G commercial wireless communication system design, from an end to end perspective. It compares and contrasts NR with LTE, and gives a concise and highly accessible description of the key technologies in the 5G physical layer, radio access network layer protocols and procedures. This book also illustrates how the 5G core and EPC is integrated into the radio access network, how virtualization and edge computer fundamentally change the way users interact with the network, as well as 5G spectrum issues. This book is structured into six chapters. The first chapter reviews the use cases, requirements, and standardization organization and activities for 5G. These are 5G requirements and not NR specifically, as technology that meets the requirements, may be submitted to the ITU as 5G technology. This includes a set of Radio Access Technologies (RATs), consisting of NR and LTE; with each RAT meeting different aspects of the requirements. The second chapter describes the air interface of NR and LTE side by side. The basic aspects of LTE that NR builds upon are first described, followed by sections on the NR specific technologies, such as carrier/channel, spectrum/duplexing (including SUL), LTE/NR co-existence and new physical layer technologies (including waveform, Polar/LDPC codes, MIMO, and URLLC/mMTC). In all cases the enhancements made relative to LTE are made apparent. The third chapter contains descriptions of NR procedures (IAM/Beam Management/Power control/HARQ), protocols (CP/UP/mobility, including grant-free), and RAN architecture. The fourth chapter includes a detailed discussion related to end-to-end system architecture, and the 5G Core (5GC), network slicing, service continuity, relation to EPC, network virtualization, and edge computing. The fifth and major chapter describes the ITU submission and how NR and LTE meet the 5G requirements in significant detail, from the rapporteur responsible for leading the preparation and evaluation, as well as some field trial results. Engineers, computer scientists and professionals with a passing knowledge of 4G LTE and a comprehensive understanding of the end to end 5G commercial wireless system will find this book to be a valuable asset. Advanced-level students and researchers studying and working in communication engineering, who want to gain an understanding of the 5G system (as well as methodologies to evaluate features and technologies intended to supplement 5G) will also find this book to be a valuable resource.

This book covers power systems cybersecurity. In order to enhance overall stability and security in wide-area cyber-physical power systems and defend against cyberattacks, new resilient operation, control, and protection methods are required. The cyberattack-resilient control methods improve overall cybersecurity and stability in normal and abnormal operating conditions. By contrast, cyberattack-resilient protection schemes are important to keep the secure operation of a system under the most severe contingencies and cyberattacks. The main subjects covered in the book are: 1) proposing new tolerant and cyberattack-resilient control and protection methods against cyberattacks for future power systems, 2) suggesting new methods for cyberattack detection and cybersecurity assessment, and 3) focusing on practical issues in modern power systems.