This book focuses on the latest emerging technologies in electric vehicles (EV), and their economic and environmental impact. The topics covered include different types of EV such as hybrid electrical vehicle (HEV), battery electrical vehicle (BEV), fuel cell electrical vehicle (FCEV), plug-in hybrid electrical vehicle (PHEV). Theoretical background and practical examples of conventional electrical machines, advanced electrical machines, battery energy sources, on-board charging and off-board charging techniques, and optimization methods are presented here. This book can be useful for students, researchers and practitioners interested in different problems and challenges associated with electric vehicles.

This book covers smart grid applications of various big data analytics, artificial intelligence, and machine learning technologies for demand prediction, decision-making processes, policy, and energy management. It delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems. In the era of propelling traditional energy systems to evolve towards smart energy systems, systems, including power generation energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic and industrial loads. Similarly, with the integration of solid-state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. Technical topics discussed in the book include: Hybrid smart energy system technologies Energy demand forecasting Use of different protocols and communication in smart energy systems Power quality and allied issues and mitigation using AI Intelligent transportation Virtual power plants AI business models

1) Complete details on IoT in Renewable Energy Systems 2) Analytics and its application in Renewable Energy Systems 3) Applications in renewable energy systems. 4) Real-time Case Studies

Multi-level Inverters (MLIs) are widely used for conversion of DC to AC power. This book provides various low-switching frequency (LSF) modulation schemes (conventional and improved), which can be implemented on MLIs. The LSF modulation schemes are implemented to three different MLI topologies to demonstrate their working and aimed at their application to reader invented MLI topologies. Highlighting the advantages of LSF over high-switching frequency (HSF) modulation schemes, the simulations are carried out using MATLAB®/Simulink along with hardware experiments. The practical application of MLIs to renewable energy sources and electric vehicles is also provided at the end of the book. Aimed at researchers, graduate students in Electric Power Engineering, Power Electronics, this book: Presents detailed overview of most commonly used multi-level invertor topologies. Covers advantages of low-switching over high-switching frequency scheme. Includes an exclusive section dedicated for an improved low-switching modulation scheme. Dedicated chapter on application of renewable energy sources to multi-level invertors and electric vehicles. Explains all the low-switching frequency modulation schemes.

This book comprises select proceedings of the international conference ETAEERE 2020, and focuses on contemporary issues in energy management and energy efficiency in the context of power systems. The contents cover modeling, simulation and optimization based studies on topics like medium voltage BTB system, cost optimization of a ring frame unit in textile industry, rectenna for RF energy harvesting, ecology and energy dimension in infrastructural designs, study of AGC in two area hydro thermal power system, energy-efficient and reliable depth-based routing protocol for underwater wireless sensor network, and power line communication. This book can be beneficial for students, researchers as well as industry professionals.

1) Complete details on IoT in Renewable Energy Systems 2) Analytics and its application in Renewable Energy Systems 3) Applications in renewable energy systems. 4) Real-time Case Studies

THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research findings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the field and create a broad knowledge about the most recent research. Series Editor Dr. Siddhartha Bhattacharyya, CHRIST (Deemed to be University), Bangalore, India Editorial Advisory Board Dr. Elizabeth Behrman, Wichita State University, Kansas, USA Dr. Goran Klepac Dr. Leo Mrsic, Algebra University College, Croatia Dr. Aboul Ella Hassanien, Cairo University, Egypt Dr. Jan Platos, VSB-Technical University of Ostrava, Czech Republic Dr. Xiao-Zhi Gao, University of Eastern Finland, Finland Dr. Wellington Pinheiro dos Santos, Federal University of Pernambuco, Brazil

The growing share of renewable energies, as well as the rising demand for electricity for transport and heating, are increasing the importance of power converters and the requirements for reliability and control. Intelligent control can increase converter efficiency, reducing size and weight. The application of intelligent control techniques to power converters has therefore recently become a focus of research. Intelligent Control of Medium and High Power Converters summarizes the state of the art in the control of electric power converters. After an overview of the topic, the chapters cover optimization, bi-directional DC-DC converters, high-gain converters, GaN-based synchronous converters, control design, sliding mode control of three-phase inverters and three-level grid-connected inverters, neurological control, low-frequency switching operation, and a comparison and overview chapter. Comparing control methods for different converters helps users find the best solution for each type of converter and application. The book is a valuable resource for researchers and manufacturers involved with converters and power grids, as well as for advanced students.

Electric vehicles (EV), are being hailed as part of the solution to reducing urban air pollution and noise, and staving off climate change. Their success hinges on the availability and reliability of fast and efficient charging facilities, both stationary and in-motion. These in turn depend on appropriate integration with the grid, load and outage management, and on the mitigation of loads using renewable energy and storage. Charging management to preserve the battery will also play a key role. This book covers the latest in charging technology; stationary as well as wireless and in-motion. Grid integration, simulations, fast charging, and battery management are also addressed. The objective of this book is to provide readers with an in-depth knowledge about EV charging infrastructure, and grid integration issues and solutions. The book serves as a reference for researchers in academia and industry, covering almost every aspect of the charging and grid integration of EVs.

Energy is a key source of economic growth due to its involvement as the primary input. Energy drives economic productivity and industrial growth. It can be considered as the prime requirement for the modern economy. Solar energy is a renewable source of energy that can be used to produce heat or generate electricity. The total amount of solar energy available on Earth’s surface is vastly in excess of the world’s current and anticipated energy requirements. In the 21st century, solar energy is expected to become increasingly attractive as a renewable energy source. An increase in the share of solar energy may destabilize the grid. To overcome the issues of grid instability, specifically in remote areas, BIM and GIS-based microgrid planning based on data can be effectively used. BIM and GIS are used to assess alternative solutions and big data analytics in building solar electrical systems according to planning requirements and managing assets. The integration of BIM and GIS information systems for microgrid planning is appealing due to its potential benefits, such as it decreases the microgrid planning time and cost. The present book is about the advancements in technology for harnessing solar energy and the challenges associated with different modes of utilizing this inexhaustible renewable energy source. This book will be helpful for researchers, academicians, technologists, innovators, and industry experts working in the area of solar energy, artificial intelligence, and smart grids.

This new volume, Deep Learning in Visual Computing and Signal Processing, covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing. The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on deep learning, and more. Key features: Covers both the fundamentals and the latest concepts in deep learning Presents some of the diverse applications of deep learning in visual computing and signal processing Includes over 90 figures and tables to elucidate the text An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this valuable resource will serve as a guide for researchers, engineers, and students who want to have a quick start on learning and/or building deep learning systems. It provides a good theoretical and practical understanding and complete information and knowledge required to understand and build deep learning models from scratch.

Energy demand will increase by 70% by the year of 2030, and with the continual day-by-day depletion of traditional energy sources, there is a vast need to continue the development of dependable renewable energy sources that are locally available and that enhance energy generation efficiency. This important resource, Deregulated Electricity Market: A Smart Grid Perspective, presents the topical issues of the deregulated electricity market, focusing on the integration of renewable sources with engineering approaches. The volume identifies and explores the deregulated electricity market s and looks at different renewable generation techniques and their operation and control issues. It considers the various power quality issues with renewable energy generation interfaced with smart grids and their solution techniques. It also addresses the various integration challenges of the energy storage systems and energy management of electric vehicles in the smart grid environment. Topics include methods for frequency, angle, and voltage monitoring in smart grids; load frequency and voltage control pricing; grid integration of wind energy generation systems; tracking and management techniques; performance analysis; and more. This volume is an important resource for scientists, researchers, students, and academicians across the globe concerned with adopting and implementing novel research on smart power grids and renewable energy systems.

The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.

Microgrids offers a complete discussion and details about microgrids and their applications, including modeling of AC/DC and hybrid grids in a tied mode with simulation for the solar systems, wind turbines, biomass and fuel cells, and deployment issues. The data communications and control mechanism implementations are analyzed for proper coordination of the AC/DC microgrid. The various real-time applications and future development of the microgrid are also discussed in this book, with MATLAB (R)-based simulations and results. This book: Discusses the fundamentals of microgrids, the components of microgrids, the modeling of renewable energy sources, and the implementation of microgrids. Explores AC and DC microgrid modeling with real-time examples. Examines the effective extraction of energy from renewable energy sources. Covers analysis of data communications and control-mechanism implementations. Includes HOMER/MATLAB (R)-based simulations and results on microgrids. This book would be a welcome addition to the libraries of researchers, senior undergraduate students, and graduate students in power and electrical engineering, especially those working with smart and microgrids.

Depletion of fossil fuels and petroleum products due to population explosion has created a tremendous demand for renewable energy sources. Non-conventional loads such as electric vehicles and smart residential systems are increasing daily, creating additional load to conventional utility grids. The extra energy demand is filled mainly by energy generated from renewable energy sources such as solar, wind and geothermal energy sources. This has meant that load distribution and power flow management have emerged as the most significant challenges for electrical engineers. Therefore, advanced power management systems must be designed to operate the present distribution system smoothly. The fourth industrial revolution has broken down the walls between the physical, digital and biological worlds. Advancements in artificial intelligence, big data, machine learning, the Internet of Things (IoT), genetic engineering, and quantum computing have made the interface between machines and users very easy. The fourth industrial revolution has brought a drastic revolution for users, from controlling battery charging to planning a suitable control technique for fabricated electrical equipment. Smooth load sharing between grid and renewable energy sources, power management as per the availability of generating sources, and circumventing the sag and swell of utility grids to operate equipment smoothly is facilitated by advanced artificial intelligent techniques. The progressive machine learning approach enables the smooth operation of machines. Overall, the fourth industrial revolution has brought enormous advantages to help electrical users. The work presented in this book deals with the advanced design methods adopted by electrical researchers to facilitate smooth utilization of the fourth industrial revolution. The content of the book includes but is not limited to the following research areas: * Topological improvement of electrical equipment to facilitate smooth user interfaces. * Improvement of techniques to tackle advanced power system problems such as sag, swell, reactive power imbalance and power flow management. * Advanced practices to facilitate smooth electric vehicle charging systems. * Grid to smart residence (G2S) and smart residence to grid (S2G) operation of the utility grid. * Stability analysis of the utility grid amid non-conventional loading. * Artificial intelligence, big data and machine learning applications to power system problems. * Intelligent controllers for an advanced residential system. * Intelligent storage systems for residential buildings.

Covers latest design and design parameters in the field of microstrip antenna. Discusses design of wearable antennas in detail. Presents design of conformal and miniaturized antenna structures for various applications. Covers methods and techniques for the enhancement of the performance parameters of the microstrip antenna. Discusses latest techniques in the field of microstrip antennas and it's applications

Discusses various aspects of role of Internet of Things (IoT) and Machine Learning in smart buildings. Explains pertinent system architecture focusing on power generation and distribution. Covers power enabling technologies for smart cities. Includes Photovoltaic System Integrated Smart Buildings.

Systematically defines energy-efficient buildings, employing power consumption optimization techniques with inclusion of renewable energy sources. Covers data centre and cyber security with excellent data storage features for smart buildings. Includes systematic and detailed strategies for building air conditioning and lighting. Details smart building security propulsion.

This book covers smart grid applications of various big data analytics, artificial intelligence, and machine learning technologies for demand prediction, decision-making processes, policy, and energy management. The book delves into new technologies such as the Internet of Things, BlockChain for smart home solutions, and smart city solutions in depth in the context of modern power systems. In the era of propelling traditional energy systems to evolve towards smart energy systems, systems, including power generation energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic and industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. Technical topics discussed in the book include: Hybrid smart energy system technologies Smart meters Energy demand forecasting Use of different protocols and communication in smart energy systems Power quality and allied issues and mitigation using AI Intelligent transportation Virtual power plants AI based smart energy business models Smart home solutions Blockchain solutions for smart grids

Presents technologies and algorithms associated with the application of big data for smart cities. Discussion on big data theory modeling and simulation for smart cities Covers applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS). Discussion on concepts including smart education, smart culture, and smart transformation management for social and societal changes.

The impact of the proposed book is to provide a significant area of concern to develop a foundation for the implementation process renewable energy system with intelligent techniques. The researchers working on a renewable energy system can correlate their work with intelligent and machine learning approaches. To make aware of the international standards for intelligent renewable energy systems design, reliability and maintenance. To give better incites of the solar cell, biofuels, wind and other renewable energy system design and characterization, including the equipment for smart energy systems.

Photovoltaic (PV) energy generation is an excellent example of large-scale electric power generation through various parallel arrangements of small voltage-generating solar cells or modules. However, PV generation systems require power electronic converters system to satisfy the need for real-time applications or to balance the demand for power from electric. Therefore, a DC-DC power converter is a vital constituent in the intermediate conversion stage of PV power. This book presents a comprehensive review of various non-isolated DC-DC power converters. Non-isolated DC-DC converters for renewable energy system (RES) application presented in this book 1st edition through a detailed original investigation, obtained numerical/experimental results, and guided the scope to design new families of converters: DC-DC multistage power converter topologies, Multistage "X-Y converter family", Nx IMBC (Nx Interleaved Multilevel Boost Converter), Cockcroft Walton (CW) Voltage Multiplier-Based Multistage/Multilevel Power Converter (CW-VM-MPC) converter topologies, and Z-source and quasi Z-source. Above solutions are discussed to show how they can achieve the maximum voltage conversion gain ratio by adapting the passive/active component within the circuits. For assessment, we have recommended novel power converters through their functionality and designs, tested and verified by numerical software. Further, the hardware prototype implementation is carried out through a flexible digital processor. Both numerical and experimental results always shown as expected close agreement with primary theoretical hypotheses. This book offers guidelines and recommendation for future development with the DC-DC converters for RES applications based on cost-effective, and reliable solutions.

Multi-level Inverters (MLIs) are widely used for conversion of DC to AC power. This book provides various low-switching frequency (LSF) modulation schemes (conventional and improved), which can be implemented on MLIs. The LSF modulation schemes are implemented to three different MLI topologies to demonstrate their working and aimed at their application to reader invented MLI topologies. Highlighting the advantages of LSF over high-switching frequency (HSF) modulation schemes, the simulations are carried out using MATLAB (R)/Simulink along with hardware experiments. The practical application of MLIs to renewable energy sources and electric vehicles is also provided at the end of the book. Aimed at researchers, graduate students in Electric Power Engineering, Power Electronics, this book: Presents detailed overview of most commonly used multi-level invertor topologies. Covers advantages of low-switching over high-switching frequency scheme. Includes an exclusive section dedicated for an improved low-switching modulation scheme. Dedicated chapter on application of renewable energy sources to multi-level invertors and electric vehicles. Explains all the low-switching frequency modulation schemes.

Microgrids offers a complete discussion and details about microgrids and their applications, including modeling of AC/DC and hybrid grids in a tied mode with simulation for the solar systems, wind turbines, biomass and fuel cells, and deployment issues. The data communications and control mechanism implementations are analyzed for proper coordination of the AC/DC microgrid. The various real-time applications and future development of the microgrid are also discussed in this book, with MATLAB (R)-based simulations and results. This book: Discusses the fundamentals of microgrids, the components of microgrids, the modeling of renewable energy sources, and the implementation of microgrids. Explores AC and DC microgrid modeling with real-time examples. Examines the effective extraction of energy from renewable energy sources. Covers analysis of data communications and control-mechanism implementations. Includes HOMER/MATLAB (R)-based simulations and results on microgrids. This book would be a welcome addition to the libraries of researchers, senior undergraduate students, and graduate students in power and electrical engineering, especially those working with smart and microgrids.