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Title
Data analytics for smart grids applications--a key to smart city development / Devendra Kumar Sharma, Rohit Sharma, Gwanggil Jeon, Raghvendra Kumar, editors.
ISBN
9783031460920 (electronic bk.)
3031460928 (electronic bk.)
9783031460913
303146091X
Published
Cham : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xxvi, 451 pages) : illustrations (chiefly color).
Item Number
10.1007/978-3-031-46092-0 doi
Call Number
TK3105
Dewey Decimal Classification
621.31
Summary
This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed December 7, 2023).
Series
Intelligent systems reference library ; v. 247. 1868-4408
Available in Other Form
Print version: 9783031460913
Data Analytics For Smart Grids And Applications - Present And Future Directions
Design, Optimization and Performance Analysis of Microgrids using Multi-Agent Q-Learning
Big Data Analytics for Smart Grid: A Review on State-of- Art Techniques and Future Directions
Smart Grid Management for Smart City Infrastructure using Wearable Sensors
Studies on Conventional and Advanced Machine Learning Algorithm towards Framing of Robust Data analytics for the Smart Grid Application
Prediction and Classification For Smart Grid Applications
A Review on Smart Metering Using Artificial Intelligence and Machine Learning Techniques: Challenges and Solutions.