Big data application in power systems
Title By: Arghandeh, Reza [Edited by] | Zhou, Yuxun [Edited by]
Material type:
BookPublisher: Amsterdam, Netherlands ; Kidlington, Oxford : Elsevier, c2018.Description: xxvi, 453 p. : ill. ; 24 cm.ISBN: 9780128119686Subject(s): Electric power systems | Smart power grids | TECHNOLOGY & ENGINEERING / Mechanical | TECHNOLOGY & ENGINEERING / ElectricalDDC classification: 004 BI GD Online resources: Location Map | Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
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| REGULAR | University of Wollongong in Dubai Main Collection | 004 BI GD (Browse shelf) | Available | T0058939 |
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| 004 BE AU Beautiful JavaScript | 004 BE CO Computer confluence : | 004 BE CO Computer confluence : | 004 BI GD Big data application in power systems | 004 BL IT IT information technology : | 004 BL MO Mobile application management | 004 BO BI Big data, little data, no data : |
A. Introduction B. Monitoring and Data Aquisition in Power Systems C. Data-Enriched Farmeworks for Smart Grid Management D. Statistical Learning Methods for Smart Grid Applications E. Present Practice for Big Data Analysis in Power Systems F. Big Data for Power System Sustainability, Security and Resiliance E. Utilities and Big Data F. Future Trends for Big Data Application In Smart Grids
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 authoritiesContains detailed references for further reading and extended researchProvides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformaticsFocuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data.