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Method for Reliability Analysis of Distribution Grid Communications Using PRMs-Monte Carlo Methods
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. KTH - Royal Institute of Technology. (PSOC)ORCID iD: 0000-0002-2014-0444
KTH, School of Electrical Engineering (EES). KTH - Royal Institute of Technology.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. KTH - Royal Institute of Technology.ORCID iD: 0000-0001-7386-7471
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. KTH - Royal Institute of Technology. (PSOC)ORCID iD: 0000-0003-3014-5609
2017 (English)Conference paper, (Refereed)
Abstract [en]

This paper presents a method to perform reliability analysis of communication systems for distribution grids. The method uses probabilistic relational models to indicate the probabilistic dependencies between the components that form the communication system and it is implemented by Monte Carlo methods. This method can be used for performing reliability predictions of simulated communication systems and for evaluating the reliability of real systems. The paper contains a case study in which the proposed method is applied to evaluate the reliability of the communication systems that are required for monitoring the network components at low voltage levels using the smart metering infrastructure. This case study is taken fromthe EU FP7 DISCERN project. Finally, the results are presented in a quantitative way, showing the individual reliability of each component and the combined reliability of the entire system.

Place, publisher, year, edition, pages
2017.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-203886OAI: oai:DiVA.org:kth-203886DiVA: diva2:1082889
Conference
IEEE Power and Energy Society (PES) General Meeting 2017, Chicago, IL
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QCR 20170406

Available from: 2017-03-19 Created: 2017-03-19 Last updated: 2017-04-06Bibliographically approved

Open Access in DiVA

No full text

Other links

http://www.pes-gm.org/2017/

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Armendariz, MikelKorman, MatusNordström, Lars
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