Artificial Intelligence For Power Electronics
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Artificial Intelligence For Power Electronics
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Author : Ahteshamul Haque
language : en
Publisher: John Wiley & Sons
Release Date : 2025-08-25
Artificial Intelligence For Power Electronics written by Ahteshamul Haque 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 2025-08-25 with Technology & Engineering categories.
Thorough review of how artificial intelligence can enhance the design, control, and optimization of power electronics systems Artificial Intelligence for Power Electronics provides a comprehensive overview of the intersection between artificial intelligence (AI) and the field of power electronics, exploring how AI can revolutionize and enhance the design, control, and optimization of power electronics systems. The book covers the fundamentals of AI, the fundamentals of power electronics and the challenges the field faces in design to production, and the solutions of these challenges through AI methods. Example solutions, along with Q&A review sections, are included throughout the text, with coverage of both Python and MATLAB. Some of the topics discussed in Artificial Intelligence for Power Electronics include: Supervised, unsupervised, and reinforcement machine learning and the role of data in training machine learning models Techniques for AI data collection in power electronics and how to clean, normalize, and handle missing values of data Optimization techniques such as Particle Swarm Optimization and Ant Colony Optimization Detection techniques for identifying faults and anomalies and clustering algorithms to group similar operational behavior Essential Python libraries for machine learning and how to perform machine learning on a Raspberry Pi Delivering an industry-specific approach to AI applications, Artificial Intelligence for Power Electronics is a helpful reference for undergraduate, postgraduate, and PhD students in electrical, electronic, and computer engineering. Mechanical engineers and other industry professionals may also find it valuable.
Ethical Artificial Intelligence In Power Electronics
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Author : Tarandeep Kaur Bhatia
language : en
Publisher: CRC Press
Release Date : 2024-08-01
Ethical Artificial Intelligence In Power Electronics written by Tarandeep Kaur Bhatia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.
This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.
Renewable Energy And Future Power Systems
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Author : Vinod Kumar Singh
language : en
Publisher: Springer Nature
Release Date : 2021-03-26
Renewable Energy And Future Power Systems written by Vinod Kumar Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-26 with Technology & Engineering categories.
This book discusses advanced technologies for applications in renewable energy and power systems. The topics covered include neural network applications in power electronics, deep learning applications in power systems, design and simulation of multilevel inverters, solid state transformers, neural network applications for fault detection in power electronics, etc. The book also discusses the important role of artificial intelligence in power systems, and machine learning for renewable energy. This book will be of interest to researchers, professionals, and technocrats looking at power systems, power distribution, and grid operations.
Ai For Power Electronics And Renewable Energy Systems
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Author : Professor Weihao Hu
language : en
Publisher: IET
Release Date : 2024-07-23
Ai For Power Electronics And Renewable Energy Systems written by Professor Weihao Hu and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-23 with Technology & Engineering categories.
This structured monograph conveys the use of AI in managing emerging power systems with distributed renewables. Coverage includes electric machine fault diagnosis, reliability control, active distribution, and management of energy systems. Numerous examples help readers understand the principles.
Artificial Intelligence Techniques In Power Systems Operations And Analysis
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Author : Nagendra Singh
language : en
Publisher: CRC Press
Release Date : 2023-08-16
Artificial Intelligence Techniques In Power Systems Operations And Analysis written by Nagendra Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-16 with Computers categories.
An electrical power system consists of a large number of generation, transmission, and distribution subsystems. It is a very large and complex system; hence, its installation and management are very difficult tasks. An electrical system is essentially a very large network with very large data sets. Handling these data sets can require much time to analyze and subsequently implement. An electrical system is necessary but also potentially very dangerous if not operated and controlled properly. The demand for electricity is ever increasing, so maintaining load demand without overloading the system poses challenges and difficulties. Thus, planning, installing, operating, and controlling such a large system requires new technology. Artificial intelligence (AI) applications have many key features that can support a power system and handle overall power system operations. AI-based applications can manage the large data sets related to a power system. They can also help design power plants, model installation layouts, optimize load dispatch, and quickly respond to control apparatus. These applications and their techniques have been successful in many areas of power system engineering. Artificial Intelligence Techniques in Power Systems Operations and Analysis focuses on the various challenges arising in power systems and how AI techniques help to overcome these challenges. It examines important areas of power system analysis and the implementation of AI-driven analysis techniques. The book helps academicians and researchers understand how AI can be used for more efficient operation. Multiple AI techniques and their application are explained. Also featured are relevant data sets and case studies. Highlights include: Power quality enhancement by PV-UPQC for non-linear load Energy management of a nanogrid through flair of deep learning from IoT environments Role of artificial intelligence and machine learning in power systems with fault detection and diagnosis AC power optimization techniques Artificial intelligence and machine learning techniques in power systems automation
Advanced And Intelligent Control In Power Electronics And Drives
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Author : Teresa Orłowska-Kowalska
language : en
Publisher: Springer
Release Date : 2014-01-08
Advanced And Intelligent Control In Power Electronics And Drives written by Teresa Orłowska-Kowalska and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-08 with Technology & Engineering categories.
Power electronics and variable frequency drives are continuously developing multidisciplinary fields in electrical engineering and it is practically not possible to write a book covering the entire area by one individual specialist. Especially by taking account the recent fast development in the neighboring fields like control theory, computational intelligence and signal processing, which all strongly influence new solutions in control of power electronics and drives. Therefore, this book is written by individual key specialist working on the area of modern advanced control methods which penetrates current implementation of power converters and drives. Although some of the presented methods are still not adopted by industry, they create new solutions with high further research and application potential. The material of the book is presented in the following three parts: Part I: Advanced Power Electronic Control in Renewable Energy Sources (Chapters 1-4), Part II: Predictive Control of Power Converters and Drives (5-7), Part III: Neurocontrol and Nonlinear Control of Power Converters and Drives (8-11). The book is intended for engineers, researchers and students in the field of power electronics and drives who are interested in the use of advanced control methods and also for specialists from the control theory area who like to explore new area of applications.
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.
Machine Learning Integration In Power Electronics
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Author : Hasan Ali Gamal Al-kaf
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Machine Learning Integration In Power Electronics written by Hasan Ali Gamal Al-kaf and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Mathematics categories.
!--StartFragment -- This book provides a comprehensive guide for integrating machine learning techniques to enhance power electronic systems, with a focus on real-time applications, fault detection, and advanced control systems. Machine learning applications in power electronics delve into the transformative potential of machine learning in the field of power electronics. It is designed for professionals, researchers, and students who seek to leverage machine learning to address complex challenges and optimize performance in power electronics. The book explores the synergies between machine learning and power electronics, highlighting the importance of these technologies in industries such as renewable energy, electric vehicles, and industrial automation. It provides practical insights into implementing machine learning solutions, covering essential concepts, algorithms, workflows, and real-time deployment. Readers can gain valuable knowledge on integration strategies and advanced applications, including control of permanent magnet synchronous motor (PMSM) drives and fault detection in neutral point clamped (NPC) inverters. Additionally, the book offers best practices for selecting appropriate machine learning methods, such as integrating physics-informed models, utilizing lightweight neural networks, ensuring transparency with explainable methods, and employing conformal prediction for reliable outcomes. Beyond practical guidance, this book presents innovative ideas from recent literature, showcasing cutting-edge applications and future research directions. With its practical focus, detailed methodologies, and forward-looking insights, this book is an essential resource for anyone looking to harness the power of machine learning to drive innovation and improve system performance in power electronics. !--EndFragment --
Intelligent Data Analytics For Power And Energy Systems
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Author : Hasmat Malik
language : en
Publisher: Springer Nature
Release Date : 2022-02-17
Intelligent Data Analytics For Power And Energy Systems written by Hasmat Malik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-17 with Technology & Engineering categories.
This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.
Applications Of Machine Learning In Power Electronics For Integration Of Renewable Energy Sources
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Author : Dr Kumar K
language : en
Publisher: Notion Press
Release Date : 2024-11-04
Applications Of Machine Learning In Power Electronics For Integration Of Renewable Energy Sources written by Dr Kumar K and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-04 with Fiction categories.
Applications of Machine Learning in Power Electronics for Integration of Renewable Energy Sources explores how AI techniques enhance renewable energy systems through optimized power electronics. This essential guide introduces machine learning applications for improving control, predictive maintenance, and fault detection across renewable sources like solar and wind. With real-world case studies and practical insights, the book equips engineers, researchers, and students with tools to tackle challenges in renewable integration, power quality, and system reliability. An invaluable resource for both beginners and experts, this book sheds light on AI-driven innovations shaping a sustainable energy future.