ISBN:
9783031460920
Language:
English
Pages:
1 Online-Ressource(XXVI, 451 p. 178 illus., 165 illus. in color.)
Edition:
1st ed. 2023.
Series Statement:
Intelligent Systems Reference Library 247
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Keywords:
Engineering
;
Computational intelligence.
;
Big data.
Abstract:
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.
Abstract:
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.
DOI:
10.1007/978-3-031-46092-0
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