Comparing probabilistic load flow methods in dealing with uncertainties at TSO/DSO interface

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Abstract

Increasing decentralized and renewable power production, which is mainly installed in distribution networks, makes planning of the transmission network more challenging. The application of probabilistic power flow methods provides additional information that can be used to predict future power flows in networks with a high share of decentralized and renewable generation. This paper compares numerical and analytical probabilistic power flow approaches focusing on the trade-off between computational time and information gain. It is shown that for the 6-bus Roy Billinton Test System, using normally distributed random variables, the analytical method is a suitable alternative to the numerical method. Reducing computational effort while retaining considerable accuracy. This makes analytical probabilistic power flow an interesting method for studying networks with a high share of decentralized and renewable generation.
Original languageEnglish
Title of host publication52nd International Universities Power Engineering Conference (UPEC)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)978-1-5386-2344-2
ISBN (Print)978-1-5386-2345-9
DOIs
Publication statusPublished - 19 Dec 2017
Event52nd International Universities' Power Engineering Conference (UPEC 2017) - Heraklion, Greece
Duration: 28 Aug 201731 Aug 2017
Conference number: 52
http://www.upec2017.com/
http://www.upec2017.com/

Conference

Conference52nd International Universities' Power Engineering Conference (UPEC 2017)
Abbreviated titleUPEC 2017
CountryGreece
CityHeraklion
Period28/08/1731/08/17
Internet address

Keywords

  • Analytical probabilistic load flow
  • TSO/DSO interface
  • Transmission network
  • Uncertainties

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