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DC Field | Value | Language |
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dc.contributor.author | Khan, M | - |
dc.contributor.author | Ashton, PM | - |
dc.contributor.author | Li, M | - |
dc.contributor.author | Taylor, GA | - |
dc.contributor.author | Pisica, I | - |
dc.contributor.author | Liu, J | - |
dc.date.accessioned | 2015-04-20T09:49:48Z | - |
dc.date.available | 2015-01-01 | - |
dc.date.available | 2015-04-20T09:49:48Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | IEEE Transactions on Smart Grid, 6 (1): 360 - 368, (January 2015) | en_US |
dc.identifier.issn | 1949-3053 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6872572 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/10595 | - |
dc.description | ("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.") | en_US |
dc.description.abstract | Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment. | en_US |
dc.format.extent | 360 - 368 | - |
dc.format.extent | 360 - 368 | - |
dc.language | eng | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.subject | Amdahl's law | en_US |
dc.subject | Detrended fluctuation analysis (DFA) | en_US |
dc.subject | Event detection | en_US |
dc.subject | Hadoop | en_US |
dc.subject | MapReduce | en_US |
dc.subject | OpenPDC | en_US |
dc.subject | Parallel computing | en_US |
dc.subject | Phasor measurement unit (PMU) | en_US |
dc.subject | Wide area monitoring systems (WAMS) | en_US |
dc.title | Parallel detrended fluctuation analysis for fast event detection on massive PMU data | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/TSG.2014.2340446 | - |
dc.relation.isPartOf | IEEE Transactions on Smart Grid | - |
dc.relation.isPartOf | IEEE Transactions on Smart Grid | - |
pubs.issue | 1 | - |
pubs.issue | 1 | - |
pubs.volume | 6 | - |
pubs.volume | 6 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Electronic and Computer Engineering/Electronic and Computer Engineering | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Energy Futures | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Energy Futures/Smart Power Networks | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups/Centre for Research into Entrepreneurship, International Business and Innovation in Emerging Markets | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute of Cancer Genetics and Pharmacogenomics | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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