Application Of Machine Learning And Deep Learning Methods To Power System Problems
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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.
Applications Of Deep Machine Learning In Future Energy Systems
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Author : Mohammad-Hassan Khooban
language : en
Publisher: Elsevier
Release Date : 2024-08-20
Applications Of Deep Machine Learning In Future Energy Systems written by Mohammad-Hassan Khooban and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Technology & Engineering categories.
Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy. - Clarifies the current state and future trends of energy system machine learning and the pitfalls facing our transitioning systems - Provides guidance on 3rd-generation AI tools for meeting the challenges of modeling and control in modern energy systems - Includes case studies and practical examples of potential applications to inspire and inform researchers and industry developers
Monitoring And Control Of Electrical Power Systems Using Machine Learning Techniques
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Author : Emilio Barocio Espejo
language : en
Publisher: Elsevier
Release Date : 2023-01-11
Monitoring And Control Of Electrical Power Systems Using Machine Learning Techniques written by Emilio Barocio Espejo and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-11 with Technology & Engineering categories.
Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms. - Covers advanced applications and solutions for monitoring and control of electrical power systems using machine learning techniques for transmission and distribution systems - Provides deep insight into power quality disturbance detection and classification through machine learning, deep learning, and spatio-temporal algorithms - Includes substantial online supplementary components focusing on dataset generation for machine learning training processes and open-source microgrid model simulators on GitHub
Intelligent Data Mining And Analysis In Power And Energy Systems
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Author : Zita A. Vale
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-13
Intelligent Data Mining And Analysis In Power And Energy Systems written by Zita A. Vale 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 2022-12-13 with Technology & Engineering categories.
Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.
Smart Grid Opportunities And Challenges In Integrating Renewable Energies
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Author : Muhammad Faizan Tahir
language : en
Publisher: Frontiers Media SA
Release Date : 2023-06-27
Smart Grid Opportunities And Challenges In Integrating Renewable Energies written by Muhammad Faizan Tahir and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-27 with Technology & Engineering categories.
Increasing Penetration Of Renewable Sources In Power Systems Opportunities And Challenges
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Author : Xue Lyu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-27
Increasing Penetration Of Renewable Sources In Power Systems Opportunities And Challenges written by Xue Lyu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-27 with Technology & Engineering categories.
Real World Challenges In Quantum Electronics And Machine Computing
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Author : Ananth, Christo
language : en
Publisher: IGI Global
Release Date : 2024-08-05
Real World Challenges In Quantum Electronics And Machine Computing written by Ananth, Christo and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Computers categories.
Quantum computers are unparalleled in terms of computational power, and they have a multitude of promising applications. However, these computers are prone to noise and instability caused by environmental interactions, making the use of these advanced machines rather impractical in most scenarios. Despite these challenges, Real-World Challenges in Quantum Electronics and Machine Computing provides innovative solutions to navigate the complexities of quantum computation, thus offering hope during this time of turbulence. By delving into the intricacies of quantum electronics and machine computing, this book equips readers with the tools to overcome the hurdles obstructing the path to practical quantum computing. It serves as a roadmap for students, practitioners, and professionals, guiding them through the intricacies of error correction techniques and hardware development. With its comprehensive coverage of cutting-edge topics and innovative solutions, the book empowers readers to tackle the most pressing challenges facing the quantum computing landscape. As researchers and engineers strive to unlock the full potential of quantum computation, this book stands as an indispensable resource, guiding them toward a future where quantum computing transcends the realm of theory and becomes a tangible reality.
Iot Machine Learning And Blockchain Technologies For Renewable Energy And Modern Hybrid Power Systems
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Author : C. Sharmeela
language : en
Publisher: CRC Press
Release Date : 2023-01-27
Iot Machine Learning And Blockchain Technologies For Renewable Energy And Modern Hybrid Power Systems written by C. Sharmeela and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-27 with Computers categories.
This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and case studies. After reading this book, users will understand recent technologies such as IoT, machine learning techniques, and blockchain technologies and the application of these technologies to renewable energy resources and modern hybrid power systems through simulation examples and case studies.
Machine Learning And Computer Vision For Renewable Energy
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Author : Acharjya, Pinaki Pratim
language : en
Publisher: IGI Global
Release Date : 2024-05-01
Machine Learning And Computer Vision For Renewable Energy written by Acharjya, Pinaki Pratim and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-01 with Technology & Engineering categories.
As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.