A smart building is the state-of-art in building with features that facilitates informed decision making based on the available data through smart metering and IoT sensors. This set provides useful information for developing smart buildings including significant improvement of energy efficiency, implementation of operational improvements and targeting sustainable environment to create an effective customer experience. It includes case studies from industrial results which provide cost effective solutions and integrates the digital SCADE solution. Describes complete implication of smart buildings via industrial, commercial and community platforms 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 set is aimed at graduate students, researchers and professionals in building systems, architectural, and electrical engineering.

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

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

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.

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

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

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.

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.

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.

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.

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

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.

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.

Presents a comprehensive discussion of mini and micro grids concepts. Discussed AC and DC micro grids modeling in detail. Covers optimization of mini and micro grid systems using AI and meta-heuristic techniques. Provides MATLAB based simulations on the mini and micro grid

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.

This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB (R) based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.

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.

Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing. Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.

The Smart Grid represents an unprecedented opportunity to move the energy industry into a new era of reliability, availability, and efficiency that will contribute to our economic and environmental health. During the transition period, it will be critical to carry out testing, technology improvements, consumer education, development of standards and regulations, and information sharing between projects to ensure that the benefits we envision from the Smart Grid become a reality. Today, an electricity disruption such as a blackout can have a domino effect-a series of failures that can affect banking, communications, traffic, and security. This is a particular threat in the winter, when homeowners can be left without heat. A smarter grid will add resiliency to our electric power system and make it better prepared to address emergencies such as severe storms, earthquakes, large solar flares, and terrorist attacks. Because of its two-way interactive capacity, the Smart Grid will allow for automatic rerouting when equipment fails or outages occur. This will minimize outages and minimize the effects when they do happen. When a power outage occurs, Smart Grid technologies will detect and isolate the outages, containing them before they become large-scale blackouts. The new technologies will also help ensure that electricity recovery resumes quickly and strategically after an emergency-routing electricity to emergency services first, for example. In addition, the Smart Grid will take greater advantage of customer-owned power generators to produce power when it is not available from utilities. By combining these "distributed generation" resources, a community could keep its health center, police department, traffic lights, phone system, and grocery stores operating during emergencies. In addition, the Smart Grid is a way to address an aging energy infrastructure that needs to be upgraded or replaced. This book shows that Smart Grids can address energy efficiency, to bring increased awareness to consumers about the connection between electricity use and the environment, bring increased national security to our energy system-drawing on greater amounts of home-grown electricity that is more resistant to natural disasters and attack.

Discusses IoT-based clean energy to automate the management of wind and solar farms. Provides solutions to diverse problems of smart grids such as load frequency and automatic generation control. Examines the challenges and techniques in improving grid security using sensor-based IoT systems. Defines smart electrical grid in managing power fluctuations with the quicker restoration of electricity. Introduces smart meters to record data on a real-time basis.