An implicit switching model for distribution network reliability assessment

Yang Yang; Simon Tindemans; Goran Strbac

doi:10.1109/PSCC.2016.7540953

An implicit switching model for distribution network reliability assessment

Yang Yang, Simon Tindemans, Goran Strbac

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and simulated using time-sequential or state sampling Monte Carlo methods. The method is illustrated on a simple distribution network, and reliability indices are reported both as averages and distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling - a method that is hard to combine with explicit switching models.

Original language	English
Title of host publication	19th Power Systems Computation Conference, PSCC 2016
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1-7
Number of pages	7
ISBN (Electronic)	978-88-941051-2-4
DOIs	https://doi.org/10.1109/PSCC.2016.7540953
Publication status	Published - 10 Aug 2016
Externally published	Yes
Event	19th Power Systems Computation Conference, PSCC 2016 - Genova, Italy Duration: 20 Jun 2016 → 24 Jun 2016

Conference

Conference	19th Power Systems Computation Conference, PSCC 2016
Country/Territory	Italy
City	Genova
Period	20/06/16 → 24/06/16

Keywords

distribution networks
Monte Carlo simulations
network topology
reliability analysis

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10.1109/PSCC.2016.7540953

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title = "An implicit switching model for distribution network reliability assessment",

abstract = "Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and simulated using time-sequential or state sampling Monte Carlo methods. The method is illustrated on a simple distribution network, and reliability indices are reported both as averages and distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling - a method that is hard to combine with explicit switching models.",

keywords = "distribution networks, Monte Carlo simulations, network topology, reliability analysis",

author = "Yang Yang and Simon Tindemans and Goran Strbac",

year = "2016",

month = aug,

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doi = "10.1109/PSCC.2016.7540953",

language = "English",

pages = "1--7",

booktitle = "19th Power Systems Computation Conference, PSCC 2016",

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T1 - An implicit switching model for distribution network reliability assessment

AU - Yang, Yang

AU - Tindemans, Simon

AU - Strbac, Goran

PY - 2016/8/10

Y1 - 2016/8/10

N2 - Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and simulated using time-sequential or state sampling Monte Carlo methods. The method is illustrated on a simple distribution network, and reliability indices are reported both as averages and distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling - a method that is hard to combine with explicit switching models.

AB - Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and simulated using time-sequential or state sampling Monte Carlo methods. The method is illustrated on a simple distribution network, and reliability indices are reported both as averages and distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling - a method that is hard to combine with explicit switching models.

KW - distribution networks

KW - Monte Carlo simulations

KW - network topology

KW - reliability analysis

UR - http://www.scopus.com/inward/record.url?scp=84986625332&partnerID=8YFLogxK

U2 - 10.1109/PSCC.2016.7540953

DO - 10.1109/PSCC.2016.7540953

M3 - Conference contribution

AN - SCOPUS:84986625332

SP - 1

EP - 7

BT - 19th Power Systems Computation Conference, PSCC 2016

PB - IEEE

CY - Piscataway, NJ

T2 - 19th Power Systems Computation Conference, PSCC 2016

Y2 - 20 June 2016 through 24 June 2016

ER -

An implicit switching model for distribution network reliability assessment

Abstract

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Keywords

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