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The present monograph offers a detailed and in-depth analysis of the topic of fault diagnosis for electric power systems and electric vehicles. First, the monograph treats the problem of Fault diagnosis with model-based and model-free techniques (Model-based fault diagnosis techniques and Model-free fault diagnosis techniques). Next, the monograph provides a solution for the problem of Control and fault diagnosis for Synchronous Generator-based renewable energy systems (Control of the marine-turbine and synchronous-generator unit and Fault diagnosis of the marine turbine and synchronous-generator unit. Additionally, the monograph introduces novel solutions for the problem of Fault diagnosis for electricity microgrids and gas processing units (Fault diagnosis for electric power DC microgrids and Fault diagnosis for electrically actuated gas compressors). Furthermore, the monograph analyzes and solves the problem of Fault diagnosis for gas and steam-turbine power generation units (Fault diagnosis for the gas-turbine and Synchronous Generator electric power unit and for the steam-turbine and synchronous generator power unit). Finally, the monograph provides a solution for the problem of Fault diagnosis for wind power units and for the distribution grid (Fault diagnosis for wind power generators and Fault diagnosis for the electric power distribution grid). The new fault detection and isolation methods that the monograph develops are of generic use and are addressed to a wide class of nonlinear dynamical systems, with emphasis on electric power systems and electric vehicles. On the one side, model-based fault detection and isolation methods are analyzed. In this case, known models about the dynamics of the monitored system are used by nonlinear state observers and Kalman Filters, which emulate the system’s fault-free condition. On the other side, model-free fault detection and isolation methods are analyzed. In this case, raw data are processed by neural networks and nonlinear regressors to generate models that emulate the fault-free condition of the monitored system. Statistical tests based on the processing of the residuals, which are formed between the outputs of the monitored system and the outputs of the fault-free model provide objective and almost infallible criteria about the occurrence of failures. The new fault detection and isolation methods with statistical procedures for defining fault thresholds enable early fault diagnosis and reveal incipient changes in the parameters of the monitored systems.
The present monograph offers a detailed and in-depth analysis of the topic of Intelligent Control for Electric Power Systems and Electric Vehicles. First, Nonlinear optimal control and Lie algebra-based control (Control based on approximate linearization and Global linearization-based control concepts) is analyzed. Next, Differential flatness theory and flatness-based control methods (Global linearization-based control with the use of differential flatness theory and Flatness-based control of nonlinear dynamical systems in cascading loops) is treated. Following the control theoretic part Control of DC and PMBLDC electric motors (Control of DC motors through a DC-DC converter and Control of Per- manent Magnet Brushless DC motors) is presented. Besides, Control of VSI-fed three-phase and multi- phase PMSMs (Nonlinear optimal control VSI-fed three-phase PMSMs and Nonlinear optimal control VSI-fed six-phase PMSMs) is explained. Additionally, Control of energy conversion chains based on PMSMs (Control of wind-turbine and PMSM-based electric power unit and Control of a PMSM-driven gas-compression unit) is studied. Besides, Control of energy conversion chains based on Induction Ma- chines (Control of the VSI-fed three-phase induction motor, Control of an induction motor-driven gas compressor and Control of induction generator-based shipboard microgrids) is explained. Next, Control of multi-phase machines in gas processing and power units (Control of gas-compressors actuated by 5-phase PMSMs and Control of 6-phase induction generators in renewable energy units) is introduced, Moreover, Control of Spherical Permanent Magnet Synchronous Motors and Switched Reluctance Mo- tors (Control of spherical permanent magnet synchronous motors, Control of switched reluctance motors for electric traction and Adaptive control for switched reluctance motors) is analyzed, Furthermore, Control of traction and powertrains in Electric Vehicles and Hybrid Electric Vehicles (Control of multi- phase motors in the traction system in electric vehicles and Control of synchronous machines and converters in power-chains of hybrid electric vehicles) is explained, Finally, Control of renewable power units and heat management units (Control of residential microgrids with Wind Generators, Fuel Cells and PVs and Control of heat pumps for thermal management in electric vehicles) it treated. The new control methods which are proposed by the monograph treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. The proposed control schemes are modular and scalable and can be applied to a large class of dynamic models of electric power systems and electric vehicles. They have a clear and easy-to- implement algorithmic part, while they also exhibit a moderate computational load. The proposed control schemes foster the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. Besides, they support the transition to electromotion and the deployment of the use of electric vehicles. The manuscript is suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels.
In the monograph on Fault diagnosis for electric power systems and electric vehicles, the following issues are analyzed: Chapter 1 is on Fault diagnosis with model-based and model-free techniques (Model-based fault diagnosis techniques and Model-free fault diagnosis techniques). Chapter 2 is on Control and fault diagnosis for Synchronous Generator-based renewable energy systems (Control of the marine-turbine and synchronous-generator unit and Fault diagnosis of the marine-turbine and synchronous-generator unit). Chapter 3 is on Fault diagnosis for electricity microgrids and gas processing units (Fault diagnosis for electric power DC microgrids and Fault diagnosis for electrically actuated gas compressors). Chapter 4 is on Fault diagnosis for gas and steam-turbine power generation units (Fault diagnosis for the gas-turbine and Synchronous Generator electric power unit). Finally, Chapter 5 is on Fault diagnosis for wind power units and the distribution grid (Fault diagnosis for wind power generators and Fault diagnosis for the electric power distribution grid).
Because society depends greatly on electric energy, power system control and protection focuses on ensuring a secure and reliable supply of power. To operate the electric systems in safe mode, the power system component should be equipped with intelligent controllers. The Handbook of Research on Smart Power System Operation and Control is a collection of innovative research on the theoretical and practical developments in smart power system operation and control that takes into account both smart grid and micro-grid systems. While highlighting topics including cybersecurity, smart grid, and wide area monitoring, this book is ideally designed for researchers, students, and industry professionals.
The reliability of induction motors is a major requirement in many industrial applications. It is especially important where an unexpected breakdown might result in the interruption of critical services such as military operations, transportation, aviation, and medical applications. Advanced Condition Monitoring and Fault Diagnosis of Electric Machines is a collection of innovative research on various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, and new trends in condition monitoring. It also pays special attention to the fault identification process. While highlighting topics including spectral analysis, electrical engineering, and bearing faults, this book is an ideal reference source for electrical engineers, mechanical engineers, researchers, and graduate-level students seeking current research on various methods of maintaining machinery.
With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condition monitoring scheme—thus improving safety and reliability in electric motor operation. It also supplies a solid foundation in the fundamentals of fault cause and effect. Combines Theoretical Analysis and Practical Application Written by experts in electrical engineering, the book approaches the fault diagnosis of electrical motors through the process of theoretical analysis and practical application. It begins by explaining how to analyze the fundamentals of machine failure using the winding functions method, the magnetic equivalent circuit method, and finite element analysis. It then examines how to implement fault diagnosis using techniques such as the motor current signature analysis (MCSA) method, frequency domain method, model-based techniques, and a pattern recognition scheme. Emphasizing the MCSA implementation method, the authors discuss robust signal processing techniques and the implementation of reference-frame-theory-based fault diagnosis for hybrid vehicles. Fault Modeling, Diagnosis, and Implementation in One Volume Based on years of research and development at the Electrical Machines & Power Electronics (EMPE) Laboratory at Texas A&M University, this book describes practical analysis and implementation strategies that readers can use in their work. It brings together, in one volume, the fundamentals of motor fault conditions, advanced fault modeling theory, fault diagnosis techniques, and low-cost DSP-based fault diagnosis implementation strategies.
This book systematically introduces readers to the core algorithms of battery management system (BMS) for electric vehicles. These algorithms cover most of the technical bottlenecks encountered in BMS applications, including battery system modeling, state of charge (SOC) and state of health (SOH) estimation, state of power (SOP) estimation, remaining useful life (RUL) prediction, heating at low temperature, and optimization of charging. The book not only presents these algorithms, but also discusses their background, as well as related experimental and hardware developments. The concise figures and program codes provided make the calculation process easy to follow and apply, while the results obtained are presented in a comparative way, allowing readers to intuitively grasp the characteristics of different algorithms. Given its scope, the book is intended for researchers, senior undergraduate and graduate students, as well as engineers in the fields of electric vehicles and energy storage.
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.
As the electrical industry continues to develop, one sector that still faces a range of concerns is the electrical distribution system. Excessive industrialization and inadequate billing are just a few issues that have plagued this electrical sector as it advances into the smart grid environment. Research is necessary to explore the possible solutions in fixing these problems and developing the distribution sector into an active and smart system. The Handbook of Research on New Solutions and Technologies in Electrical Distribution Networks is a collection of innovative research on the methods and applications of solving major issues within the electrical distribution system. Some issues covered within the publication include distribution losses, improper monitoring of system, renewable energy integration with micro-grid and distributed energy sources, and smart home energy management system modelling. This book is ideally designed for power engineers, electrical engineers, energy professionals, developers, technologists, policymakers, researchers, academicians, industry professionals, and students seeking current research on improving this key sector of the electrical industry.
Smart grid and microgrid technology are growing exponentially as they are adopted throughout the world. These new technologies have revolutionized the way electricity is produced, delivered, and consumed, and offer a plethora of benefits as well as the potential for further growth. It is critical to examine the current stage of smart grid and microgrid development as well as the direction they are headed as they continue to expand in order to ensure that cost-effective, reliable, and efficient systems are put in place. The Research Anthology on Smart Grid and Microgrid Development is an all-encompassing reference source of the latest innovations and trends within smart grid and microgrid development. Detailing benefits, challenges, and opportunities, it is a crucial resource to fully understand the current opportunities that smart grids and microgrids present around the world. Covering a wide range of topics such as traditional grids, future smart grids, electrical distribution systems, and microgrid integration, it is ideal for engineers, policymakers, systems developers, technologists, researchers, government officials, academicians, environmental groups, regulators, utilities specialists, industry professionals, and students.