Data Science Of Renewable Energy Integration
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Data Science Of Renewable Energy Integration
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Author : Yuichi Ikeda
language : en
Publisher: Springer Nature
Release Date : 2024-02-20
Data Science Of Renewable Energy Integration written by Yuichi Ikeda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-20 with Business & Economics categories.
This book covers various data scientific approaches to analyze the issue of grid integration of renewable energy for which the grid flexibility is the key to cope with its intermittency. It provides readers with the scope to view renewable energy integration as establishing a distributed energy network instead of the traditional centralized energy system. Specifically, quantitative valuation system-wise of the levelized cost of energy, which includes both initial cost and various operational costs, enables readers to optimize energy systems in order to minimize economic cost and environmental impact. It is noted, however, that the high cost of integrating renewable energy on a large scale might slow economic growth considerably. Topics addressed in the book also include statistical comparative study of the relationship between energy and economic growth, a graphical model of determinant factors for foreign direct investment in renewable energy, the coupled oscillator model and unitcommitment model to capture intermittency of renewable energy, and the network model of evolving micro-grids. The book explains desired innovation to reduce the integration cost significantly using innovative technologies such as energy storage with hydrogen production and vehicle-to-grid technology. Illustrated by careful analysis of selected examples of renewable integration using different types of grid flexibility, this volume is indispensable to readers who make policy recommendations to establish the distributed energy network integrated with large-scale renewable energy by disentangling the nexus of energy, environment, and economic growth.
Renewable Energy Integration
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Author : Jahangir Hossain
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-29
Renewable Energy Integration written by Jahangir Hossain and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-29 with Technology & Engineering categories.
This book presents different aspects of renewable energy integration, from the latest developments in renewable energy technologies to the currently growing smart grids. The importance of different renewable energy sources is discussed, in order to identify the advantages and challenges for each technology. The rules of connecting the renewable energy sources have also been covered along with practical examples. Since solar and wind energy are the most popular forms of renewable energy sources, this book provides the challenges of integrating these renewable generators along with some innovative solutions. As the complexity of power system operation has been raised due to the renewable energy integration, this book also includes some analysis to investigate the characteristics of power systems in a smarter way. This book is intended for those working in the area of renewable energy integration in distribution networks.
Data Analytics For Renewable Energy Integration
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Author : Wei Lee Woon
language : en
Publisher: Springer
Release Date : 2017-01-18
Data Analytics For Renewable Energy Integration written by Wei Lee Woon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.
This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held in Riva del Garda, Italy, in September 2016. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
Renewable Energy Integration
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Author : Lawrence E. Jones
language : en
Publisher: Academic Press
Release Date : 2014-06-12
Renewable Energy Integration written by Lawrence E. Jones and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-12 with Business & Economics categories.
Renewable Energy Integration is a ground-breaking new resource - the first to offer a distilled examination of the intricacies of integrating renewables into the power grid and electricity markets. It offers informed perspectives from internationally renowned experts on the challenges to be met and solutions based on demonstrated best practices developed by operators around the world. The book's focus on practical implementation of strategies provides real-world context for theoretical underpinnings and the development of supporting policy frameworks. The book considers a myriad of wind, solar, wave and tidal integration issues, thus ensuring that grid operators with low or high penetration of renewable generation can leverage the victories achieved by their peers. Renewable Energy Integration highlights, carefully explains, and illustrates the benefits of advanced technologies and systems for coping with variability, uncertainty, and flexibility. - Lays out the key issues around the integration of renewables into power grids and markets, from the intricacies of operational and planning considerations, to supporting regulatory and policy frameworks - Provides global case studies that highlight the challenges of renewables integration and present field-tested solutions - Illustrates enabling and disruptive technologies to support the management of variability, uncertainty and flexibility
Data Analytics For Renewable Energy Integration Informing The Generation And Distribution Of Renewable Energy
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Author : Wei Lee Woon
language : en
Publisher: Springer
Release Date : 2017-11-24
Data Analytics For Renewable Energy Integration Informing The Generation And Distribution Of Renewable Energy written by Wei Lee Woon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-24 with Computers categories.
This book constitutes revised selected papers from the 5th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2017, held in Skopje, Macedonia, in September 2017. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
Data Analytics For Renewable Energy Integration
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Author : Wei Lee Woon
language : en
Publisher: Springer
Release Date : 2014-11-20
Data Analytics For Renewable Energy Integration written by Wei Lee Woon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-20 with Computers categories.
This book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
Data Analytics For Renewable Energy Integration Technologies Systems And Society
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Author : Wei Lee Woon
language : en
Publisher: Springer
Release Date : 2018-11-16
Data Analytics For Renewable Energy Integration Technologies Systems And Society written by Wei Lee Woon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Computers categories.
This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018. The 9 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response, and many others.
Applications Of Ai And Iot In Renewable Energy
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Author : Rabindra Nath Shaw
language : en
Publisher: Elsevier
Release Date : 2022-02-14
Applications Of Ai And Iot In Renewable Energy written by Rabindra Nath Shaw and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-14 with Science categories.
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
Data Science And Applications For Modern Power Systems
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Author : Le Xie
language : en
Publisher: Springer Nature
Release Date : 2023-06-20
Data Science And Applications For Modern Power Systems written by Le Xie and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-20 with Technology & Engineering categories.
This book offers a comprehensive collection of research articles that utilize data—in particular large data sets—in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid.
Machine Learning And Data Science In The Power Generation Industry
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Author : Patrick Bangert
language : en
Publisher: Elsevier
Release Date : 2021-01-14
Machine Learning And Data Science In The Power Generation Industry written by Patrick Bangert and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Technology & Engineering categories.
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