Parameter Identification Approach to Series DC Arc Fault Detection and Localization

Luis Herrera; Xiu Yao

doi:10.1109/ECCE.2018.8557679

Parameter Identification Approach to Series DC Arc Fault Detection and Localization

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

In this paper, series dc arc fault localization within a system of parallel loads in a distribution node is investigated. The high frequency noise of series arc can travel to adjacent loads possibly triggering multiple detectors. To accurate localize the faulted line/load, a parameter identification technique based on a gradient algorithm with projection is used. The main goals of this approach is to monitor the condition of the line parameters, including its resistance and inductance. By identifying these values, it is possible to accurately determine the faulted line even when large noise from series arc is present. Simulation and experimental results are conducted to verify the proposed algorithm.

Original language	English
Title of host publication	2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	497-501
Number of pages	5
ISBN (Electronic)	9781479973118
DOIs	https://doi.org/10.1109/ECCE.2018.8557679
State	Published - Dec 3 2018
Event	10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 - Portland, United States Duration: Sep 23 2018 → Sep 27 2018

Publication series

Name	2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018

Conference

Conference	10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018
Country/Territory	United States
City	Portland
Period	09/23/18 → 09/27/18

Access to Document

10.1109/ECCE.2018.8557679

Cite this

Herrera, L., & Yao, X. (2018). Parameter Identification Approach to Series DC Arc Fault Detection and Localization. In 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018 (pp. 497-501). Article 8557679 (2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2018.8557679

@inproceedings{2756724b4d7c408981b21173240a2579,

title = "Parameter Identification Approach to Series DC Arc Fault Detection and Localization",

abstract = "In this paper, series dc arc fault localization within a system of parallel loads in a distribution node is investigated. The high frequency noise of series arc can travel to adjacent loads possibly triggering multiple detectors. To accurate localize the faulted line/load, a parameter identification technique based on a gradient algorithm with projection is used. The main goals of this approach is to monitor the condition of the line parameters, including its resistance and inductance. By identifying these values, it is possible to accurately determine the faulted line even when large noise from series arc is present. Simulation and experimental results are conducted to verify the proposed algorithm.",

author = "Luis Herrera and Xiu Yao",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 ; Conference date: 23-09-2018 Through 27-09-2018",

year = "2018",

month = dec,

day = "3",

doi = "10.1109/ECCE.2018.8557679",

language = "English",

series = "2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Herrera, L & Yao, X 2018, Parameter Identification Approach to Series DC Arc Fault Detection and Localization. in 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018., 8557679, 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 497-501, 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018, Portland, United States, 09/23/18. https://doi.org/10.1109/ECCE.2018.8557679

Parameter Identification Approach to Series DC Arc Fault Detection and Localization. / Herrera, Luis ; Yao, Xiu.
2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 497-501 8557679 (2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper, series dc arc fault localization within a system of parallel loads in a distribution node is investigated. The high frequency noise of series arc can travel to adjacent loads possibly triggering multiple detectors. To accurate localize the faulted line/load, a parameter identification technique based on a gradient algorithm with projection is used. The main goals of this approach is to monitor the condition of the line parameters, including its resistance and inductance. By identifying these values, it is possible to accurately determine the faulted line even when large noise from series arc is present. Simulation and experimental results are conducted to verify the proposed algorithm.

AB - In this paper, series dc arc fault localization within a system of parallel loads in a distribution node is investigated. The high frequency noise of series arc can travel to adjacent loads possibly triggering multiple detectors. To accurate localize the faulted line/load, a parameter identification technique based on a gradient algorithm with projection is used. The main goals of this approach is to monitor the condition of the line parameters, including its resistance and inductance. By identifying these values, it is possible to accurately determine the faulted line even when large noise from series arc is present. Simulation and experimental results are conducted to verify the proposed algorithm.

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ER -

Parameter Identification Approach to Series DC Arc Fault Detection and Localization

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