Applications Of Deep Machine Learning In Future Energy Systems

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Applications of Deep Machine Learning in Future Energy Systems

Author : Mohammad-Hassan Khooban
Publisher : Elsevier
ISBN 13 : 044321431X
Total Pages : 336 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Applications of Deep Machine Learning in Future Energy Systems by : Mohammad-Hassan Khooban

Download or read book Applications of Deep Machine Learning in Future Energy Systems written by Mohammad-Hassan Khooban and published by Elsevier. This book was released on 2024-08-20 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Machine Learning for Energy Systems

Author : Denis Sidorov
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.

Artificial Intelligence for Renewable Energy Systems

Author : Ajay Kumar Vyas
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.

Applications of AI and IOT in Renewable Energy

Author : Rabindra Nath Shaw
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

Intelligent Renewable Energy Systems

Author : Neeraj Priyadarshi
Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Intelligent Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and published by John Wiley & Sons. This book was released on 2022-01-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Application of Machine Learning and Deep Learning Methods to Power System Problems

Author : Morteza Nazari-Heris
Publisher : Springer Nature
ISBN 13 : 3030776964
Total Pages : 391 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Application of Machine Learning and Deep Learning Methods to Power System Problems by : Morteza Nazari-Heris

Download or read book Application of Machine Learning and Deep Learning Methods to Power System Problems written by Morteza Nazari-Heris and published by Springer Nature. This book was released on 2021-11-21 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Renewable Energy and Future Power Systems

Author : Vinod Kumar Singh
Publisher : Springer Nature
ISBN 13 : 9813367539
Total Pages : 271 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis Renewable Energy and Future Power Systems by : Vinod Kumar Singh

Download or read book Renewable Energy and Future Power Systems written by Vinod Kumar Singh and published by Springer Nature. This book was released on 2021-03-26 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applications of Big Data and Artificial Intelligence in Smart Energy Systems

Author : Neelu Nagpal
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.

Markov Decision Processes

Author : Martin L. Puterman
Publisher : John Wiley & Sons
ISBN 13 : 1118625870
Total Pages : 544 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Markov Decision Processes by : Martin L. Puterman

Download or read book Markov Decision Processes written by Martin L. Puterman and published by John Wiley & Sons. This book was released on 2014-08-28 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential." —Zentralblatt fur Mathematik ". . . it is of great value to advanced-level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic. . . . Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes." —Journal of the American Statistical Association

Intelligent Data Mining and Analysis in Power and Energy Systems

Author : Zita A. Vale
Publisher : John Wiley & Sons
ISBN 13 : 1119834023
Total Pages : 500 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Intelligent Data Mining and Analysis in Power and Energy Systems by : Zita A. Vale

Download or read book Intelligent Data Mining and Analysis in Power and Energy Systems written by Zita A. Vale and published by John Wiley & Sons. This book was released on 2022-12-13 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning Applications, Volume 2

Author : M. Arif Wani
Publisher : Springer
ISBN 13 : 9789811567582
Total Pages : 300 pages
Book Rating : 4.5/5 (675 download)

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Book Synopsis Deep Learning Applications, Volume 2 by : M. Arif Wani

Download or read book Deep Learning Applications, Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Enabling Secure Subsurface Storage in Future Energy Systems

Author : J.M. Miocic
Publisher : Geological Society of London
ISBN 13 : 1786205769
Total Pages : 507 pages
Book Rating : 4.7/5 (862 download)

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Book Synopsis Enabling Secure Subsurface Storage in Future Energy Systems by : J.M. Miocic

Download or read book Enabling Secure Subsurface Storage in Future Energy Systems written by J.M. Miocic and published by Geological Society of London. This book was released on 2023-08-31 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: The secure storage of energy and carbon dioxide in subsurface geological formations plays a crucial role in transitioning to a low-carbon energy system. The suitability and security of subsurface storage sites rely on the geological and hydraulic properties of the reservoir and confining units. Additionally, their ability to withstand varying thermal, mechanical, hydraulic, biological and chemical conditions during storage operations is essential. Each subsurface storage technology has distinct geological requirements and faces specific economic, logistical, public and scientific challenges. As a result, certain sites can be better suited than others for specific low-carbon energy applications. This Special Publication provides a summary of the state of the art in subsurface energy and carbon dioxide storage. It includes 20 case studies that offer insights into site selection, characterization of reservoir processes, the role of caprocks and fault seals, as well as monitoring and risk assessment needs for subsurface storage operations.

Grid Modernization ─ Future Energy Network Infrastructure

Author : Mohammadreza Daneshvar
Publisher : Springer Nature
ISBN 13 : 303064099X
Total Pages : 293 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Grid Modernization ─ Future Energy Network Infrastructure by : Mohammadreza Daneshvar

Download or read book Grid Modernization ─ Future Energy Network Infrastructure written by Mohammadreza Daneshvar and published by Springer Nature. This book was released on 2021-03-08 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents theoretical, technical, and practical information on the modernization of future energy networks. All the basic requirements covering concepts, modeling, optimizing, and analyzing of future energy grids with various energy carriers such as electricity, gas, heat, and water, as well as their markets and contracts, are explained in detail. The main focus of the book is on modernizing both the energy consumers and the energy producers and analyzing various aspects of grid modernization such as reliability, resiliency, stability, and security. Coverage includes advanced communication protocols and solution methods for the Internet of Energy (IoE) infrastructure and energy trading in future energy grids with high/full share of renewable energy resources (RERs) within the transactive energy (TE) paradigm. Probabilistic modeling and optimizing of modern grids will be evaluated using realistic case studies considering the economic aspects of multi-carrier energy markets. This book will be welcomed as an important resource by researchers and postgraduate students studying energy systems, as well as practicing engineers working on modernizing energy grids and the design, planning, scheduling, and operation of smart power systems. Proposes practical solutions for solving the challenges of modern multi-carrier energy grids; Examines various types of energy storage systems and distributed energy resources (DERs) with an emphasis on renewable energy resources (RERs); Provides comprehensive mathematical models for optimizing of future modern multi-carrier energy grids.

Machine Learning and Deep Learning in Real-Time Applications

Author : Mahrishi, Mehul
Publisher : IGI Global
ISBN 13 : 1799830977
Total Pages : 344 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Machine Learning and Deep Learning in Real-Time Applications by : Mahrishi, Mehul

Download or read book Machine Learning and Deep Learning in Real-Time Applications written by Mahrishi, Mehul and published by IGI Global. This book was released on 2020-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data Application in Power Systems

Author : Reza Arghandeh
Publisher : Elsevier
ISBN 13 : 0128119691
Total Pages : 482 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Big Data Application in Power Systems by : Reza Arghandeh

Download or read book Big Data Application in Power Systems written by Reza Arghandeh and published by Elsevier. This book was released on 2017-11-27 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Modeling, Analysis, and Control of Smart Energy Systems

Author : Naoui, Mohamed
Publisher : IGI Global
ISBN 13 :
Total Pages : 357 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Modeling, Analysis, and Control of Smart Energy Systems by : Naoui, Mohamed

Download or read book Modeling, Analysis, and Control of Smart Energy Systems written by Naoui, Mohamed and published by IGI Global. This book was released on 2024-08-08 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing demand for cleaner and more intelligent energy solutions poses a challenge that resonates across academic, engineering, and policymaking spheres. The complexity of integrating renewable energy sources, energy storage solutions, and advanced communication technologies demands a comprehensive understanding, rigorous analysis, and innovative control strategies. The academic community, in particular, seeks a guiding light through this intricate maze of evolving energy dynamics. Modeling, Analysis, and Control of Smart Energy Systems is a groundbreaking publication that offers more than theoretical exploration; it is a roadmap equipped with the knowledge and tools required to shape the future of energy systems. From laying conceptual foundations to unraveling real-world case studies, the book seamlessly bridges the gap between theory and application. Its comprehensive coverage of mathematical modeling, dynamic system analysis, intelligent control strategies, and the integration of renewable energy sources positions it as an authoritative reference for researchers, engineers, and policymakers alike.

Machine Learning for Sustainable Development

Author : Kamal Kant Hiran
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110702517
Total Pages : 214 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Machine Learning for Sustainable Development by : Kamal Kant Hiran

Download or read book Machine Learning for Sustainable Development written by Kamal Kant Hiran and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-07-19 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.