001     892612
005     20230531203012.0
024 7 _ |a 10.1109/ACCESS.2021.3076892
|2 doi
024 7 _ |a 2128/27960
|2 Handle
024 7 _ |a WOS:000649562100001
|2 WOS
037 _ _ |a FZJ-2021-02201
082 _ _ |a 621.3
100 1 _ |a Kaiser, Franz
|0 P:(DE-Juel1)176610
|b 0
|e Corresponding author
245 _ _ |a Universal statistics of redistribution factors and large scale cascades in power grids
260 _ _ |a New York, NY
|c 2021
|b IEEE
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1623863479_13181
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Cascades of failures are among the biggest threats to supply networks such as power grids: An initially failing element may trigger the failure of other elements, thereby eventually causing the entire network to collapse. Here, we analyse the statistics of Line Outage Distribution Factors (LODFs), which describe the rerouting of electric power flows after a line failure. In particular, we demonstrate that absolute LODFs are approximately log-normally distributed throughout network topologies. We then illustrate that this log-normal distribution of redistribution factors results in a heavy tailed distribution of outage sizes in a simplified, stochastic cascade model over a certain range of parameters. This cascade model extends previous stochastic cascade models by adding more realistic redistribution mechanisms as well as including more realistic initial trigger events. Our results demonstrate that the statistics of redistribution factors is a fundamental trait throughout different networks and presents a possible explanation for the vast occurrence of heavy tailed distributions in real-world reanalyses of power outage sizes.
536 _ _ |a 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153)
|0 G:(DE-HGF)POF3-153
|c POF3-153
|f POF III
|x 0
536 _ _ |a 1112 - Societally Feasible Transformation Pathways (POF4-111)
|0 G:(DE-HGF)POF4-1112
|c POF4-111
|f POF IV
|x 1
536 _ _ |a VH-NG-1025 - Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" (VH-NG-1025_20112014)
|0 G:(HGF)VH-NG-1025_20112014
|c VH-NG-1025_20112014
|x 2
536 _ _ |a CoNDyNet 2 - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (BMBF-03EK3055B)
|0 G:(DE-JUEL1)BMBF-03EK3055B
|c BMBF-03EK3055B
|x 3
536 _ _ |a ES2050 - Energie System 2050 (ES2050)
|0 G:(DE-HGF)ES2050
|c ES2050
|x 4
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Witthaut, Dirk
|0 P:(DE-Juel1)162277
|b 1
773 _ _ |a 10.1109/ACCESS.2021.3076892
|g Vol. 9, p. 67364 - 67378
|0 PERI:(DE-600)2687964-5
|p 67364 - 67378
|t IEEE access
|v 9
|y 2021
|x 2169-3536
856 4 _ |u https://juser.fz-juelich.de/record/892612/files/09420052.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:892612
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)176610
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)162277
913 0 _ |a DE-HGF
|b Energie
|l Technologie, Innovation und Gesellschaft
|1 G:(DE-HGF)POF3-150
|0 G:(DE-HGF)POF3-153
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-100
|4 G:(DE-HGF)POF
|v Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security
|x 0
913 1 _ |a DE-HGF
|b Forschungsbereich Energie
|l Energiesystemdesign (ESD)
|1 G:(DE-HGF)POF4-110
|0 G:(DE-HGF)POF4-111
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-100
|4 G:(DE-HGF)POF
|v Energiesystemtransformation
|9 G:(DE-HGF)POF4-1112
|x 0
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1230
|2 StatID
|b Current Contents - Electronics and Telecommunications Collection
|d 2021-01-28
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b IEEE ACCESS : 2019
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2021-01-28
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-28
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2021-01-28
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2021-01-28
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2021-01-28
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2021-01-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2021-01-28
915 p c |a APC keys set
|2 APC
|0 PC:(DE-HGF)0000
915 p c |a Local Funding
|2 APC
|0 PC:(DE-HGF)0001
915 p c |a DFG OA Publikationskosten
|2 APC
|0 PC:(DE-HGF)0002
915 p c |a DOAJ Journal
|2 APC
|0 PC:(DE-HGF)0003
920 _ _ |l no
920 1 _ |0 I:(DE-Juel1)IEK-STE-20101013
|k IEK-STE
|l Systemforschung und Technologische Entwicklung
|x 0
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IEK-STE-20101013
980 _ _ |a APC


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21