Big Data Application in Power Systems

Big Data Application in Power Systems
Author :
Publisher : Elsevier
Total Pages : 450
Release :
ISBN-10 : 9780443219511
ISBN-13 : 0443219516
Rating : 4/5 (516 Downloads)

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 2024-07-01 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data


Big Data Application in Power Systems Related Books

Big Data Application in Power Systems
Language: en
Pages: 450
Authors: Reza Arghandeh
Categories: Technology & Engineering
Type: BOOK - Published: 2024-07-01 - Publisher: Elsevier

DOWNLOAD EBOOK

Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big dat
Advanced Data Analytics for Power Systems
Language: en
Pages: 601
Authors: Ali Tajer
Categories: Computers
Type: BOOK - Published: 2021-04-08 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to pow
Big Data Analytics in Future Power Systems
Language: en
Pages: 189
Authors: Ahmed F. Zobaa
Categories: Science
Type: BOOK - Published: 2018-08-14 - Publisher: CRC Press

DOWNLOAD EBOOK

Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a hu
Decision Making Applications in Modern Power Systems
Language: en
Pages: 578
Authors: Shady Abdel Aleem
Categories: Science
Type: BOOK - Published: 2019-09-21 - Publisher: Academic Press

DOWNLOAD EBOOK

Decision Making Applications in Modern Power Systems presents an enhanced decision-making framework for power systems. Designed as an introduction to enhanced e
Big Data Analytics Strategies for the Smart Grid
Language: en
Pages: 258
Authors: Carol L. Stimmel
Categories: Computers
Type: BOOK - Published: 2014-07-25 - Publisher: CRC Press

DOWNLOAD EBOOK

By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally ef