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The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning: book chapter. / Stepanova, Alina.
Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023: book. Institute of Electrical and Electronics Engineers Inc., 2023. p. 94-99.

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

Harvard

Stepanova, A 2023, The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning: book chapter. in Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023: book. Institute of Electrical and Electronics Engineers Inc., pp. 94-99, 2023 Belarusian-Ural-Siberian Smart Energy Conference (BUSSEC), Екатеринбург, Russian Federation, 25/09/2023. https://doi.org/10.1109/BUSSEC59406.2023.10296227

APA

Stepanova, A. (2023). The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning: book chapter. In Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023: book (pp. 94-99). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BUSSEC59406.2023.10296227

Vancouver

Stepanova A. The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning: book chapter. In Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023: book. Institute of Electrical and Electronics Engineers Inc. 2023. p. 94-99 doi: 10.1109/BUSSEC59406.2023.10296227

Author

Stepanova, Alina. / The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning : book chapter. Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023: book. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 94-99

BibTeX

@inproceedings{a42b0e00d88847c19baa6ac7497a989e,
title = "The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning: book chapter",
abstract = "The paper presents the methodology for assessing the technical state of high-voltage power transmission lines, based on the decomposition method with the application of gradient boosting on decision tress. The decomposition method presupposes separate assessment of the technical state of the different structural parts of the high-voltage power transmission line: insulation, tower, span, tower footing, high-frequency filter. The total score of the structural parts' technical state is calculated by aggregation of the sub-elements' values of each structural part. The article demonstrates the application of the decomposition method, based on data obtained as a result of technical diagnostics of the high-voltage power transmission lines of 110 kV. As a result of the assessment of the technical state of the high-voltage transmission line, editorial changes were noted for the formation of the database. The paper highlights the existing barriers in regulatory documentation in the field of determining the boundaries between different technical states. The authors provide suggestions and recommendations on regulatory documentation improvement to foster the implementation of intelligent monitoring systems in power grids. {\textcopyright} 2023 IEEE.",
author = "Alina Stepanova",
note = "The reported study was supported by Russian Science Foundation, research project No. 22-79-10315.; 2023 Belarusian-Ural-Siberian Smart Energy Conference (BUSSEC) ; Conference date: 25-09-2023 Through 29-09-2023",
year = "2023",
doi = "10.1109/BUSSEC59406.2023.10296227",
language = "English",
isbn = "979-835035807-0",
pages = "94--99",
booktitle = "Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - The Methodology for Overhead Power Transmission Lines Technical State Assessment Based on Machine Learning

T2 - 2023 Belarusian-Ural-Siberian Smart Energy Conference (BUSSEC)

AU - Stepanova, Alina

N1 - The reported study was supported by Russian Science Foundation, research project No. 22-79-10315.

PY - 2023

Y1 - 2023

N2 - The paper presents the methodology for assessing the technical state of high-voltage power transmission lines, based on the decomposition method with the application of gradient boosting on decision tress. The decomposition method presupposes separate assessment of the technical state of the different structural parts of the high-voltage power transmission line: insulation, tower, span, tower footing, high-frequency filter. The total score of the structural parts' technical state is calculated by aggregation of the sub-elements' values of each structural part. The article demonstrates the application of the decomposition method, based on data obtained as a result of technical diagnostics of the high-voltage power transmission lines of 110 kV. As a result of the assessment of the technical state of the high-voltage transmission line, editorial changes were noted for the formation of the database. The paper highlights the existing barriers in regulatory documentation in the field of determining the boundaries between different technical states. The authors provide suggestions and recommendations on regulatory documentation improvement to foster the implementation of intelligent monitoring systems in power grids. © 2023 IEEE.

AB - The paper presents the methodology for assessing the technical state of high-voltage power transmission lines, based on the decomposition method with the application of gradient boosting on decision tress. The decomposition method presupposes separate assessment of the technical state of the different structural parts of the high-voltage power transmission line: insulation, tower, span, tower footing, high-frequency filter. The total score of the structural parts' technical state is calculated by aggregation of the sub-elements' values of each structural part. The article demonstrates the application of the decomposition method, based on data obtained as a result of technical diagnostics of the high-voltage power transmission lines of 110 kV. As a result of the assessment of the technical state of the high-voltage transmission line, editorial changes were noted for the formation of the database. The paper highlights the existing barriers in regulatory documentation in the field of determining the boundaries between different technical states. The authors provide suggestions and recommendations on regulatory documentation improvement to foster the implementation of intelligent monitoring systems in power grids. © 2023 IEEE.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85178018681

U2 - 10.1109/BUSSEC59406.2023.10296227

DO - 10.1109/BUSSEC59406.2023.10296227

M3 - Conference contribution

SN - 979-835035807-0

SP - 94

EP - 99

BT - Proceedings of the 2023 Belarusian-Ural-Siberian Smart Energy Conference, BUSSEC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 25 September 2023 through 29 September 2023

ER -

ID: 49262247