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Method for Reliability Analysis of Distribution Grid Communications Using PRMs-Monte Carlo Methods
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0002-2014-0444
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0001-7386-7471
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. KTH, Superseded Departments (pre-2005), Electrical Systems.ORCID iD: 0000-0003-3014-5609
2017 (English)In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE , 2017Conference paper, Published 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 from the 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
IEEE , 2017.
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
Keywords [en]
Communication systems for distribution grids, Monte Carlo, probabilistic relational models, reliability analysis
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:kth:diva-228180ISI: 000426921803135ISBN: 978-1-5386-2212-4 OAI: oai:DiVA.org:kth-228180DiVA, id: diva2:1208984
Conference
2017 IEEE Power & Energy Society General Meeting, JUL 16-20, 2017, Chicago, IL
Note

QC 20180521

Available from: 2018-05-21 Created: 2018-05-21 Last updated: 2018-05-21Bibliographically approved

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Other links

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

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Armendariz, MikelKorman, MatusNordström, Lars

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