Deep Learning For Power System Applications
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Application Of Machine Learning And Deep Learning Methods To Power System Problems
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Author : Morteza Nazari-Heris
language : en
Publisher: Springer Nature
Release Date : 2021-10-20
Application Of Machine Learning And Deep Learning Methods To Power System Problems written by Morteza Nazari-Heris and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-20 with Technology & Engineering categories.
This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.
Deep Learning For Power System Applications
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Author : Fangxing Li
language : en
Publisher: Springer Nature
Release Date : 2023-11-10
Deep Learning For Power System Applications written by Fangxing Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Technology & Engineering categories.
This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control. Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers. Provides a history of AI in power grid operation and planning; Introduces deep learning algorithms and applications in power systems; Includes several representative case studies.
Power System State Estimation
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Author : Ali Abur
language : en
Publisher: CRC Press
Release Date : 2004-03-24
Power System State Estimation written by Ali Abur and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-24 with Technology & Engineering categories.
Offering an up-to-date account of the strategies utilized in state estimation of electric power systems, this text provides a broad overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational efficiency. Includes numerous tutorial examples that fully analyze problems posed by the inclusion of current measurements in existing state estimators and illustrate practical solutions to these challenges. Written by two expert researchers in the field, Power System State Estimation extensively details topics never before covered in depth in any other text, including novel robust state estimation methods, estimation of parameter and topology errors, and the use of ampere measurements for state estimation. It introduces various methods and computational issues involved in the formulation and implementation of the weighted least squares (WLS) approach, presents statistical tests for the detection and identification of bad data in system measurements, and reveals alternative topological and numerical formulations for the network observability problem.
Deep Learning Applications And Intelligent Decision Making In Engineering
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Author : Karthikrajan Senthilnathan
language : en
Publisher:
Release Date : 2020
Deep Learning Applications And Intelligent Decision Making In Engineering written by Karthikrajan Senthilnathan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computational intelligence categories.
"This book explores the application of deep learning in building a smart world, ranging from smart cities, smart agriculture to smart homes"--
Machine Learning And Deep Learning In Real Time Applications
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Author : Paawan Sharma
language : en
Publisher: Engineering Science Reference
Release Date : 2020
Machine Learning And Deep Learning In Real Time Applications written by Paawan Sharma and has been published by Engineering Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.
Intelligent Renewable Energy Systems
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Author : Neeraj Priyadarshi
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-29
Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-29 with Computers categories.
INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.
Big Data Application In Power Systems
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Author : Reza Arghandeh
language : en
Publisher: Elsevier
Release Date : 2024-07-01
Big Data Application In Power Systems written by Reza Arghandeh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-01 with Technology & Engineering categories.
Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data
Computational Intelligence In Power Engineering
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Author : Bijaya Ketan Panigrahi
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-20
Computational Intelligence In Power Engineering written by Bijaya Ketan Panigrahi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-20 with Computers categories.
This volume deals with different computational intelligence (CI) techniques for solving real world power industry problems. It will be extremely helpful for the researchers as well as the practicing engineers in the power industry.
Artificial Intelligence Techniques In Power Systems
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Author : Kevin Warwick
language : en
Publisher: IET
Release Date : 1997
Artificial Intelligence Techniques In Power Systems written by Kevin Warwick and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
The intention of this book is to give an introduction to, and an overview of, the field of artificial intelligence techniques in power systems, with a look at various application studies.
Applications Of Computational Intelligence To Power Systems
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Author : Vassilis S. Kodogiannis
language : en
Publisher: MDPI
Release Date : 2019-11-08
Applications Of Computational Intelligence To Power Systems written by Vassilis S. Kodogiannis and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-08 with Technology & Engineering categories.
Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.