Machine Learning and Data Science in the Power Generation Industry

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Author :
Publisher : Elsevier
ISBN 13 : 0128226005
Total Pages : 276 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Machine Learning and Data Science in the Power Generation Industry by : Patrick Bangert

Download or read book Machine Learning and Data Science in the Power Generation Industry written by Patrick Bangert and published by Elsevier. This book was released on 2021-01-14 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls

Machine Learning and Data Science in the Oil and Gas Industry

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Publisher : Gulf Professional Publishing
ISBN 13 : 0128209143
Total Pages : 290 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Machine Learning and Data Science in the Oil and Gas Industry by : Patrick Bangert

Download or read book Machine Learning and Data Science in the Oil and Gas Industry written by Patrick Bangert and published by Gulf Professional Publishing. This book was released on 2021-03-04 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Advances of Machine Learning in Clean Energy and the Transportation Industry

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Publisher :
ISBN 13 : 9781685072117
Total Pages : pages
Book Rating : 4.0/5 (721 download)

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Book Synopsis Advances of Machine Learning in Clean Energy and the Transportation Industry by : Pandian Vasant

Download or read book Advances of Machine Learning in Clean Energy and the Transportation Industry written by Pandian Vasant and published by . This book was released on 2021-11-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research in the field of machine learning, discussing the real-world application problems associated with new innovative renewable energy methodologies as well as cutting edge technologies in the transport industry. The requirements and demands of problem solving have been increasing exponentially, and new artificial intelligence and machine learning technologies have reduced the scope of data coverage worldwide. Recent advances in data technology (DT) have contributed to reducing the gaps in the coverage of domains around the globe.Attention to clean energy in recent decades has been growing exponentially. This is mainly due to a decrease in the cost of both installed capacity of converters and a decrease in the cost of generated energy. Such successes were achieved thanks to the improvement of modern technologies for the production of converters, an increase in the efficiency of using incoming energy, optimization of the operation of converters and analysis of data obtained during the operation of systems with the possibility of planning production. The use of clean energy plays an important role in the transportation industry, where technologies are also being improved from year to year - the transportation industry is growing, and machinery and systems are becoming more autonomous and robotic, where it is no longer possible to do without complex intelligent computing, machine learning optimization, planning and working with large amounts of data.The book is a valuable reference work for researchers in the fields of renewable energy, computer science and engineering with a particular focus on machine learning and intelligent optimization as well as for postgraduates, managers, economists and decision makers, policy makers, government officials, industrialists and practicing scientists and engineers as well compassionate global decision makers. Topics include: Machine learning, Quantum Optimization, Modern Technology in Transport Industry, Innovative Technologies in Transport Education, Systems Based on Renewable Energy Conversion, Business Process Models and Applications in Renewable Energy, Clean Energy, and Climate Change.

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

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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.

Advances in Information and Communication

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Publisher : Springer Nature
ISBN 13 : 303098012X
Total Pages : 952 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Advances in Information and Communication by : Kohei Arai

Download or read book Advances in Information and Communication written by Kohei Arai and published by Springer Nature. This book was released on 2022-03-07 with total page 952 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book “Advances in Information and Communication Networks - Proceedings of the 2022 Future of Information and Communication Conference (FICC)” aims in presenting the latest research advances, sharing expert knowledge and exchanging ideas with the common goal of shaping the future of Information and Communication. The conference attracted 402 submissions, of which, 131 submissions (including six poster papers) have been selected through a double-blind review process by an international panel of expert referees. This book discusses on aspects of Communication, Data Science, Ambient Intelligence, Networking, Computing, Security and Internet of Things, from classical to intelligent scope. The intention is to help academic pioneering researchers, scientists, industrial engineers, and students become familiar with and stay abreast of the ever-changing technology surrounding their industry. We hope that readers find the volume interesting and valuable; it gathers chapters addressing state-of-the-art intelligent methods and techniques for solving real world problems along with a vision of the future research.

Big Data Application in Power Systems

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Publisher : Elsevier
ISBN 13 : 0128119691
Total Pages : 480 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 480 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

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.

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

Artificial Intelligence, Machine Learning, and Data Science Technologies

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Publisher : CRC Press
ISBN 13 : 1000460525
Total Pages : 311 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Artificial Intelligence, Machine Learning, and Data Science Technologies by : Neeraj Mohan

Download or read book Artificial Intelligence, Machine Learning, and Data Science Technologies written by Neeraj Mohan and published by CRC Press. This book was released on 2021-10-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

Encyclopedia of Data Science and Machine Learning

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Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Intelligent Renewable Energy Systems

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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.

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.

AI-Powered IoT in the Energy Industry

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Publisher : Springer Nature
ISBN 13 : 3031150449
Total Pages : 318 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis AI-Powered IoT in the Energy Industry by : S. Vijayalakshmi

Download or read book AI-Powered IoT in the Energy Industry written by S. Vijayalakshmi and published by Springer Nature. This book was released on 2023-04-05 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. ​Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.

Artificial Intelligence for Renewable Energy Systems

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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.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

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Publisher : Academic Press
ISBN 13 : 0323914284
Total Pages : 418 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies by : Krishna Kumar

Download or read book Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies written by Krishna Kumar and published by Academic Press. This book was released on 2022-03-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

Artificial Intelligence and Data Analytics for Energy Exploration and Production

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Publisher : John Wiley & Sons
ISBN 13 : 1119879876
Total Pages : 613 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Artificial Intelligence and Data Analytics for Energy Exploration and Production by : Fred Aminzadeh

Download or read book Artificial Intelligence and Data Analytics for Energy Exploration and Production written by Fred Aminzadeh and published by John Wiley & Sons. This book was released on 2022-08-26 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

Applications of Big Data and Artificial Intelligence in Smart Energy Systems

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Author :
Publisher : CRC Press
ISBN 13 : 1000963829
Total Pages : 318 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 2023-09-29 with total page 318 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, domestic loads, and 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 & 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 for modern power systems such as the Internet of Things, Blockchain for smart home and smart city solutions in depth. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Smart meters • 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 based smart energy business models • Smart home solutions • Blockchain solutions for smart grids.