Automated analysis of power systems disturbance records: smart grid big data perspective
Analysis of faults and disturbances play crucial roles in secure and reliable electrical power supply. Digital fault recorders (DFR) enable digital recording of the power systems transient events with high quality and huge quantity. However, transformation of data to information, expectedly in...
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sg-ntu-dr.10356-967672020-03-07T13:24:47Z Automated analysis of power systems disturbance records: smart grid big data perspective Ukil, Abhisek Zivanovic, Rastko School of Electrical and Electronic Engineering IEEE Innovative Smart Grid Technical Conference, ISGT Asia (2014:Kuala Lumpur) DRNTU::Engineering::Electrical and electronic engineering Analysis of faults and disturbances play crucial roles in secure and reliable electrical power supply. Digital fault recorders (DFR) enable digital recording of the power systems transient events with high quality and huge quantity. However, transformation of data to information, expectedly in an automated way, is a big challenge for the power utilities worldwide. This is a key focus for realizing the ‘Smart Grid’. In this paper, the architecture and specifications for the primary and the secondary information for the automated systems are described. This provides qualitative and quantitative guidelines about the information to derive out of the disturbance data. A quantified estimate of big data for the substations, has been estimated in the paper. Possible ways of reducing the big data by utilizing intelligent segmentation techniques are described, substantiated by real example. Utilization of centralized protection and remote disturbance analysis for reducing big disturbance data are also discussed. Accepted version 2014-08-21T01:40:33Z 2019-12-06T19:34:49Z 2014-08-21T01:40:33Z 2019-12-06T19:34:49Z 2014 2014 Conference Paper Ukil, A., & Zivanovic, R. (2014). Automated analysis of power systems disturbance records: smart grid big data perspective. IEEE Innovative Smart Grid Technical Conference., ISGT ASIA 2014. Kuala Lumpur, Malaysia. https://hdl.handle.net/10356/96767 http://hdl.handle.net/10220/20356 10.1109/ISGT-Asia.2014.6873776 en © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ISGT-Asia.2014.6873776]. 6 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Ukil, Abhisek Zivanovic, Rastko Automated analysis of power systems disturbance records: smart grid big data perspective |
description |
Analysis of faults and disturbances play crucial
roles in secure and reliable electrical power supply. Digital
fault recorders (DFR) enable digital recording of the power
systems transient events with high quality and huge quantity.
However, transformation of data to information, expectedly in
an automated way, is a big challenge for the power utilities
worldwide. This is a key focus for realizing the ‘Smart Grid’. In
this paper, the architecture and specifications for the primary
and the secondary information for the automated systems are
described. This provides qualitative and quantitative guidelines
about the information to derive out of the disturbance data.
A quantified estimate of big data for the substations, has been
estimated in the paper. Possible ways of reducing the big data
by utilizing intelligent segmentation techniques are described,
substantiated by real example. Utilization of centralized
protection and remote disturbance analysis for reducing big
disturbance data are also discussed. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Ukil, Abhisek Zivanovic, Rastko |
format |
Conference or Workshop Item |
author |
Ukil, Abhisek Zivanovic, Rastko |
author_sort |
Ukil, Abhisek |
title |
Automated analysis of power systems disturbance records: smart grid big data perspective |
title_short |
Automated analysis of power systems disturbance records: smart grid big data perspective |
title_full |
Automated analysis of power systems disturbance records: smart grid big data perspective |
title_fullStr |
Automated analysis of power systems disturbance records: smart grid big data perspective |
title_full_unstemmed |
Automated analysis of power systems disturbance records: smart grid big data perspective |
title_sort |
automated analysis of power systems disturbance records: smart grid big data perspective |
publishDate |
2014 |
url |
https://hdl.handle.net/10356/96767 http://hdl.handle.net/10220/20356 |
_version_ |
1681042213240307712 |