Fault indicator placement optimization using the cross-entropy method and traffic simulation data

M. L. Cardoso; L. F. Venturini; Y. L. Baracy; I. M.B. Ulisses; L. E. Bremermann; A. P. Grilo-Pavani; L. M. Carvalho; D. Issicaba

doi:10.1016/j.epsr.2022.108391

Fault indicator placement optimization using the cross-entropy method and traffic simulation data

M. L. Cardoso, L. F. Venturini, Y. L. Baracy, I. M.B. Ulisses, L. E. Bremermann, A. P. Grilo-Pavani, L. M. Carvalho, D. Issicaba

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks.

Original language	English
Article number	108391
Journal	Electric Power Systems Research
Volume	212
DOIs	https://doi.org/10.1016/j.epsr.2022.108391
Publication status	Published - Nov 2022
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.

Funding

This work was developed in Project F-LOCO with Grupo Energisa, under the framework of the Research and Development (R&D) Program regulated by Agencia Nacional de Energia Elétrica (ANEEL), code PD-00405-1804/2018. This work was supported in part by the Brazilian National Council for Scientific and Technological Development (CNPq), part by the Coordination for the Improvement of Higher Level Personnel (CAPES), Brazil – Finance Code 001, and part by the Institute of Systems and Computer Engineering, Research and Development of Brazil (INESC P&D Brasil). This work was developed in Project F-LOCO with Grupo Energisa, under the framework of the Research and Development (R&D) Program regulated by Agencia Nacional de Energia Elétrica (ANEEL), code PD-00405-1804/2018. This work was supported in part by the Brazilian National Council for Scientific and Technological Development (CNPq) , part by the Coordination for the Improvement of Higher Level Personnel (CAPES), Brazil – Finance Code 001 , and part by the Institute of Systems and Computer Engineering, Research and Development of Brazil (INESC P&D Brasil) .

Funders	Funder number
INESC
Institute of Systems and Computer Engineering, Research and Development of Brazil
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Agência Nacional de Energia Elétrica	PD-00405-1804/2018

Keywords

Cross-entropy
Fault indicator
Monte Carlo simulation
Power distribution
Traffic simulation

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10.1016/j.epsr.2022.108391

Cite this

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title = "Fault indicator placement optimization using the cross-entropy method and traffic simulation data",

abstract = "This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks.",

keywords = "Cross-entropy, Fault indicator, Monte Carlo simulation, Power distribution, Traffic simulation",

author = "Cardoso, {M. L.} and Venturini, {L. F.} and Baracy, {Y. L.} and Ulisses, {I. M.B.} and Bremermann, {L. E.} and Grilo-Pavani, {A. P.} and Carvalho, {L. M.} and D. Issicaba",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.",

year = "2022",

month = nov,

doi = "10.1016/j.epsr.2022.108391",

language = "English",

volume = "212",

journal = "Electric Power Systems Research",

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AU - Cardoso, M. L.

AU - Venturini, L. F.

AU - Baracy, Y. L.

AU - Ulisses, I. M.B.

AU - Bremermann, L. E.

AU - Grilo-Pavani, A. P.

AU - Carvalho, L. M.

AU - Issicaba, D.

PY - 2022/11

Y1 - 2022/11

N2 - This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks.

AB - This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks.

KW - Cross-entropy

KW - Fault indicator

KW - Monte Carlo simulation

KW - Power distribution

KW - Traffic simulation

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DO - 10.1016/j.epsr.2022.108391

M3 - Article

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SN - 0378-7796

VL - 212

JO - Electric Power Systems Research

JF - Electric Power Systems Research

M1 - 108391

ER -

Fault indicator placement optimization using the cross-entropy method and traffic simulation data

Abstract

Bibliographical note

Funding

Keywords

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