Computer Vision and Machine Intelligence for Renewable Energy Systems

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Author :
Publisher : Elsevier
ISBN 13 : 0443289476
Total Pages : 388 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Computer Vision and Machine Intelligence for Renewable Energy Systems by : Ashutosh Kumar Dubey

Download or read book Computer Vision and Machine Intelligence for Renewable Energy Systems written by Ashutosh Kumar Dubey and published by Elsevier. This book was released on 2024-10 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision and Machine Intelligence in Renewable Energy Systems, the first release in Elsevier's cutting-edge new series, Advances in Intelligent Energy Systems, offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration. The book equips readers with a variety of essential tools and applications, outlining the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence and breaking down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Other sections offer case studies and applications to a wide range of renewable energy source and the future possibilities of the technology. This book provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.

Computer Vision and Machine Intelligence for Renewable Energy Systems

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Author :
Publisher : Elsevier
ISBN 13 : 0443289484
Total Pages : 389 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Computer Vision and Machine Intelligence for Renewable Energy Systems by : Ashutosh Kumar Dubey

Download or read book Computer Vision and Machine Intelligence for Renewable Energy Systems written by Ashutosh Kumar Dubey and published by Elsevier. This book was released on 2024-09-20 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source

Machine Learning and Computer Vision for Renewable Energy

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Author :
Publisher : IGI Global
ISBN 13 :
Total Pages : 351 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Machine Learning and Computer Vision for Renewable Energy by : Acharjya, Pinaki Pratim

Download or read book Machine Learning and Computer Vision for Renewable Energy written by Acharjya, Pinaki Pratim and published by IGI Global. This book was released on 2024-05-01 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence for Renewable Energy systems

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Author :
Publisher : Woodhead Publishing
ISBN 13 : 0323906613
Total Pages : 408 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence for Renewable Energy systems by : Ashutosh Kumar Dubey

Download or read book Artificial Intelligence for Renewable Energy systems written by Ashutosh Kumar Dubey and published by Woodhead Publishing. This book was released on 2022-08-01 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms. - Includes real-time applications that illustrates artificial intelligence and machine learning for various renewable systems - Features a templated approach that can be used to explore results, with scientific implications followed by detailed case studies - Covers computational capabilities and varieties for renewable system design

Artificial Intelligence and Internet of Things for Renewable Energy Systems

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Author :
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110714043
Total Pages : 318 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Artificial Intelligence and Internet of Things for Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Artificial Intelligence and Internet of Things for Renewable Energy Systems written by Neeraj Priyadarshi and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-11-22 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains the application of Artificial Intelligence and Internet of Things on green energy systems. The design of smart grids and intelligent networks enhances energy efficiency, while the collection of environmental data through sensors and their prediction through machine learning models improve the reliability of green energy systems.

Explainable Artificial Intelligence and Solar Energy Integration

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Author :
Publisher : IGI Global
ISBN 13 :
Total Pages : 506 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Explainable Artificial Intelligence and Solar Energy Integration by : Pandey, Jay Kumar

Download or read book Explainable Artificial Intelligence and Solar Energy Integration written by Pandey, Jay Kumar and published by IGI Global. This book was released on 2024-10-16 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: As sustainable energy becomes the future, integrating solar power into existing systems presents critical challenges. Intelligent solutions are required to optimize energy production while maintaining transparency, reliability, and trust in decision-making processes. The growing complexity of these systems calls for advanced technologies that can ensure efficiency while addressing the unique demands of renewable energy sources. Explainable Artificial Intelligence and Solar Energy Integration explores how Explainable AI (XAI) enhances transparency in AI-driven solutions for solar energy integration. By showcasing XAI's role in improving energy efficiency and sustainability, the book bridges the gap between AI potential and real-world solar energy applications. It serves as a comprehensive resource for researchers, engineers, policymakers, and students, offering both technical insights and practical case studies.

Applications of AI and IOT in Renewable Energy

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Publisher : Academic Press
ISBN 13 : 0323984010
Total Pages : 248 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Applications of AI and IOT in Renewable Energy by : Rabindra Nath Shaw

Download or read book Applications of AI and IOT in Renewable Energy written by Rabindra Nath Shaw and published by Academic Press. This book was released on 2022-02-09 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy

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Author :
Publisher : Springer Nature
ISBN 13 : 3031264967
Total Pages : 302 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy by : Mukhdeep Singh Manshahia

Download or read book Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy written by Mukhdeep Singh Manshahia and published by Springer Nature. This book was released on 2023-06-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.

Introduction to AI Techniques for Renewable Energy System

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Publisher : CRC Press
ISBN 13 : 1000392457
Total Pages : 423 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Introduction to AI Techniques for Renewable Energy System by : Suman Lata Tripathi

Download or read book Introduction to AI Techniques for Renewable Energy System written by Suman Lata Tripathi and published by CRC Press. This book was released on 2021-11-25 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

IoT, Machine Learning and Blockchain Technologies for Renewable Energy and Modern Hybrid Power Systems

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Publisher : CRC Press
ISBN 13 : 1000824403
Total Pages : 305 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis IoT, Machine Learning and Blockchain Technologies for Renewable Energy and Modern Hybrid Power Systems by : C. Sharmeela

Download or read book IoT, Machine Learning and Blockchain Technologies for Renewable Energy and Modern Hybrid Power Systems written by C. Sharmeela and published by CRC Press. This book was released on 2023-01-27 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Quantum Computing and Artificial Intelligence

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110791404
Total Pages : 308 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Quantum Computing and Artificial Intelligence by : Pethuru Raj

Download or read book Quantum Computing and Artificial Intelligence written by Pethuru Raj and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-08-21 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Renewable Energy Systems

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Publisher : Academic Press
ISBN 13 : 0128203986
Total Pages : 734 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Renewable Energy Systems by : Ahmad Taher Azar

Download or read book Renewable Energy Systems written by Ahmad Taher Azar and published by Academic Press. This book was released on 2021-09-09 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems by leading researchers. The book brings together the most comprehensive collection of modeling, control theorems and optimization techniques to help solve many scientific issues for researchers in renewable energy and control engineering. Many multidisciplinary applications are discussed, including new fundamentals, modeling, analysis, design, realization and experimental results. The book also covers new circuits and systems to help researchers solve many nonlinear problems. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. - Covers modeling, control theorems and optimization techniques which will solve many scientific issues for researchers in renewable energy - Discusses many multidisciplinary applications with new fundamentals, modeling, analysis, design, realization and experimental results - Includes new circuits and systems, helping researchers solve many nonlinear problems

Design, Analysis and Applications of Renewable Energy Systems

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Publisher : Academic Press
ISBN 13 : 0323859917
Total Pages : 762 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Design, Analysis and Applications of Renewable Energy Systems by : Ahmad Taher Azar

Download or read book Design, Analysis and Applications of Renewable Energy Systems written by Ahmad Taher Azar and published by Academic Press. This book was released on 2021-09-09 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, Analysis and Applications of Renewable Energy Systems covers recent advancements in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems as conveyed by leading energy systems engineering researchers. The book focuses on present novel solutions for many problems in the field, covering modeling, control theorems and the optimization techniques that will help solve many scientific issues for researchers. Multidisciplinary applications are also discussed, along with their fundamentals, modeling, analysis, design, realization and experimental results. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. - Presents some of the latest innovative approaches to renewable energy systems from the point-of-view of dynamic modeling, system analysis, optimization, control and circuit design - Focuses on advances related to optimization techniques for renewable energy and forecasting using machine learning methods - Includes new circuits and systems, helping researchers solve many nonlinear problems

Applications of Big Data and Artificial Intelligence in Smart Energy Systems

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Publisher : CRC Press
ISBN 13 : 1000963977
Total Pages : 250 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Applications of Big Data and Artificial Intelligence in Smart Energy Systems by : Neelu Nagpal

Download or read book Applications of Big Data and Artificial Intelligence in Smart Energy Systems written by Neelu Nagpal and published by CRC Press. This book was released on 2023-11-23 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of propelling traditional energy systems to evolve towards smart energy 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 & 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. This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book 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. 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.

Artificial Intelligence for Smart and Sustainable Energy Systems and Applications

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Author :
Publisher : MDPI
ISBN 13 : 303928889X
Total Pages : 258 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Artificial Intelligence for Smart and Sustainable Energy Systems and Applications by : Miltiadis D. Lytras

Download or read book Artificial Intelligence for Smart and Sustainable Energy Systems and Applications written by Miltiadis D. Lytras and published by MDPI. This book was released on 2020-05-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.

Artificial Intelligence for Renewable Energy Systems

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119761697
Total Pages : 276 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Artificial Intelligence for Renewable Energy Systems by : Ajay Kumar Vyas

Download or read book Artificial Intelligence for Renewable Energy Systems written by Ajay Kumar Vyas and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

Machine Learning for Energy Systems

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Author :
Publisher : MDPI
ISBN 13 : 3039433822
Total Pages : 272 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Machine Learning for Energy Systems by : Denis Sidorov

Download or read book Machine Learning for Energy Systems written by Denis Sidorov and published by MDPI. This book was released on 2020-12-08 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.