Soft Computing in Green and Renewable Energy Systems
Soft Computing in Green and Renewable Energy Systems

Author: Kasthurirangan Gopalakrishnan

Publisher: Springer Science & Business Media

Published: 2011-08-20

Total Pages: 315

ISBN-13: 3642221750

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Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.

Soft Computing in Renewable Energy Technologies
Soft Computing in Renewable Energy Technologies

Author: Najib El Ouanjli

Publisher: CRC Press

Published: 2024-10-10

Total Pages: 228

ISBN-13: 1040121942

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This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

Intelligent and Soft Computing Systems for Green Energy
Intelligent and Soft Computing Systems for Green Energy

Author: A. Chitra

Publisher: John Wiley & Sons

Published: 2023-05-15

Total Pages: 388

ISBN-13: 1394167504

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INTELLIGENT AND SOFT COMPUTING SYSTEMS FOR GREEN ENERGY Written and edited by some of the world’s top experts in the field, this exciting new volume provides state-of-the-art research and the latest technological breakthroughs in next-generation computing systems for the energy sector, striving to bring the science toward sustainability. Real-world problems need intelligent solutions. Across many industries and fields, intelligent and soft computing systems, using such developing technologies as artificial intelligence and Internet of Things, are quickly becoming important tools for scientists, engineers, and other professionals for solving everyday problems in practical situations. This book aims to bring together the research that has been carried out in the field of intelligent and soft computing systems. Intelligent and soft computing systems involves expertise from various domains of research, such as electrical engineering, computer engineering, and mechanical engineering. This book will serve as a point of convergence wherein all these domains come together. The various chapters are configured to address the challenges faced in intelligent and soft computing systems from various fields and possible solutions. The outcome of this book can serve as a potential resource for industry professionals and researchers working in the domain of intelligent and soft computing systems. To list a few soft computing techniques, neural-based load forecasting, IoT-enabled smart grids, and blockchain technology for energy trading. Whether for the veteran engineer or the student learning the latest breakthroughs, this exciting new volume is a must-have for any library.

Applied Soft Computing and Embedded System Applications in Solar Energy
Applied Soft Computing and Embedded System Applications in Solar Energy

Author: Rupendra Kumar Pachauri

Publisher: CRC Press

Published: 2021-05-27

Total Pages: 258

ISBN-13: 1000391736

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Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor – Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.

Solar PV and Wind Energy Conversion Systems
Solar PV and Wind Energy Conversion Systems

Author: S. Sumathi

Publisher: Springer

Published: 2016-10-06

Total Pages: 0

ISBN-13: 9783319366937

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This textbook starts with a review of the principles of operation, modeling and control of common solar energy and wind-power generation systems before moving on to discuss grid compatibility, power quality issues and hybrid models of Solar PV and Wind Energy Conversion Systems (WECS). MATLAB/SIMULINK models of fuel cell technology and associated converters are discussed in detail. The impact of soft computing techniques such as neural networks, fuzzy logic and genetic algorithms in the context of solar and wind energy is explained with practical implementation using MATLAB/SIMULINK models. This book is intended for final year undergraduate, post-graduate and research students interested in understanding the modeling and control of Solar PV and Wind Energy Conversion Systems based on MATLAB/SIMULINK. - Each chapter includes “Learning Objectives” at the start, a “Summary” at the end and helpful Review Questions - Includes MATLAB/SIMULINK models of different control strategies for power conditioning units in the context of Solar PV - Presents soft computing techniques for Solar PV and WECS, as well as MATLAB/SIMULINK models, e.g. for wind turbine topologies and grid integration - Covers hybrid solar PV and Wind Energy Conversion Systems with converters and MATLAB/SIMULINK models - Reviews harmonic reduction in Solar PV and Wind Energy Conversion Systems in connection with power quality issues - Covers fuel cells and converters with implementation using MATLAB/SIMULINK

Advances of Artificial Intelligence in a Green Energy Environment
Advances of Artificial Intelligence in a Green Energy Environment

Author: Pandian Vasant

Publisher: Academic Press

Published: 2022-05-20

Total Pages: 416

ISBN-13: 0323885748

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Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry. - Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide - Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms - Includes flowchart diagrams for exampling optimizing techniques

Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid
Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid

Author: Hazra, Sunanda

Publisher: IGI Global

Published: 2024-07-17

Total Pages: 520

ISBN-13:

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Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.

Applications of AI and IOT in Renewable Energy
Applications of AI and IOT in Renewable Energy

Author: Rabindra Nath Shaw

Publisher: Academic Press

Published: 2022-02-09

Total Pages: 248

ISBN-13: 0323984010

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Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. - Includes future applications of AI and IOT in renewable energy - Based on case studies to give each chapter real-life context - Provides advances in renewable energy using AI and IOT with technical detail and data

The Green Computing Book
The Green Computing Book

Author: Wu-chun Feng

Publisher: CRC Press

Published: 2014-06-16

Total Pages: 358

ISBN-13: 1439819874

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State-of-the-Art Approaches to Advance the Large-Scale Green Computing Movement Edited by one of the founders and lead investigator of the Green500 list, The Green Computing Book: Tackling Energy Efficiency at Large Scale explores seminal research in large-scale green computing. It begins with low-level, hardware-based approaches and then traverses up the software stack with increasingly higher-level, software-based approaches. In the first chapter, the IBM Blue Gene team illustrates how to improve the energy efficiency of a supercomputer by an order of magnitude without any system performance loss in parallelizable applications. The next few chapters explain how to enhance the energy efficiency of a large-scale computing system via compiler-directed energy optimizations, an adaptive run-time system, and a general prediction performance framework. The book then explores the interactions between energy management and reliability and describes storage system organization that maximizes energy efficiency and reliability. It also addresses the need for coordinated power control across different layers and covers demand response policies in computing centers. The final chapter assesses the impact of servers on data center costs.