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  • This paper deals with usage of multivariate statistical analyses methods as tools for simulation reliability of distribution network. At present a description of a feeder failure is created by the help of dependence of a number of failures on length of the feeder, i.e. specific failure rate, which quite mismatch, because even two the same long lines can have different count of failures per annum. Analysis uses at description one's feeder more attributes. Preferred methods for description of feeders groups are a cluster analysis (CLU) and a principal component analysis (PCA). At the end of the paper there is a comparison between performed simulation of SAIFI with negative binomial distribution and values provided by the technique which divides feeders according to their lengths. Then a search for the dependencies between attributes and feeders division is described.
  • This paper deals with usage of multivariate statistical analyses methods as tools for simulation reliability of distribution network. At present a description of a feeder failure is created by the help of dependence of a number of failures on length of the feeder, i.e. specific failure rate, which quite mismatch, because even two the same long lines can have different count of failures per annum. Analysis uses at description one's feeder more attributes. Preferred methods for description of feeders groups are a cluster analysis (CLU) and a principal component analysis (PCA). At the end of the paper there is a comparison between performed simulation of SAIFI with negative binomial distribution and values provided by the technique which divides feeders according to their lengths. Then a search for the dependencies between attributes and feeders division is described. (en)
Title
  • Possibilities of using multi - dimensional statistical analyses methods when evaluating reliability of distribution network
  • Possibilities of using multi - dimensional statistical analyses methods when evaluating reliability of distribution network (en)
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  • Possibilities of using multi - dimensional statistical analyses methods when evaluating reliability of distribution network
  • Possibilities of using multi - dimensional statistical analyses methods when evaluating reliability of distribution network (en)
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  • RIV/00216305:26220/10:PU87876!RIV11-MPO-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(2A-2TP1/051)
http://linked.open...vai/riv/dodaniDat
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  • 280253
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/10:PU87876
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  • Cluster Analysis, CLU, Principal Component Analysis, PCA, Distribution Network (en)
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http://linked.open...ontrolniKodProRIV
  • [659B0FECE5AA]
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  • Hotel Santon, Brno
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  • Brno
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  • Proceedings of the 11th International Scientific Conference Electric Power Engineering 2010
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
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  • Toman, Petr
  • Geschwinder, Lukáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • Vysoké učení technické v Brně
https://schema.org/isbn
  • 978-80-214-4094-4
http://localhost/t...ganizacniJednotka
  • 26220
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