Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks

Mert Kesici; Can Berk Saner; Mohammed Mahdi; Yusuf Yaslan; V. M.Istemihan Genc

doi:10.1109/SGCF.2019.8782365

Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks

Mert Kesici, Can Berk Saner, Mohammed Mahdi, Yusuf Yaslan, V. M.Istemihan Genc

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

8 Citations (Scopus)

Abstract

Online monitoring of the power system is a vital application for enhancing the situational awareness capabilities of the system. Rapid integration of phasor measurement units in the network enables transmission system operators to analyze the events in real time due to their high reporting rates. Real-time detection and classification of the fault related events as no-fault, fault-incidence, fault-on and post-fault stage with no further disturbance, is an important requirement in order to decide on the control actions to protect the system from any instability. In this paper, a sliding window based continuous online monitoring method of the power system using convolutional neural networks is proposed. The effectiveness of the proposed method is validated on the 127-bus Western Systems Coordinating Council test system.

Original language	English
Title of host publication	7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings
Editors	Aydin Cetin
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	223-227
Number of pages	5
ISBN (Electronic)	9781728113159
DOIs	https://doi.org/10.1109/SGCF.2019.8782365
Publication status	Published - Apr 2019
Event	7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Istanbul, Turkey Duration: 25 Apr 2019 → 26 Apr 2019

Publication series

Name	7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings

Conference

Conference	7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019
Country/Territory	Turkey
City	Istanbul
Period	25/04/19 → 26/04/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Funding

ACKNOWLEDGMENT This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under grant number 118E184.

Funders	Funder number
TUBITAK	118E184
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Keywords

Classification
deep learning
online monitoring
power system monitoring

Access to Document

10.1109/SGCF.2019.8782365

Cite this

Kesici, M., Saner, C. B., Mahdi, M., Yaslan, Y., & Genc, V. M. I. (2019). Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks. In A. Cetin (Ed.), 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings (pp. 223-227). Article 8782365 (7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SGCF.2019.8782365

Kesici, Mert ; Saner, Can Berk ; Mahdi, Mohammed et al. / Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks. 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings. editor / Aydin Cetin. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 223-227 (7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings).

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title = "Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks",

abstract = "Online monitoring of the power system is a vital application for enhancing the situational awareness capabilities of the system. Rapid integration of phasor measurement units in the network enables transmission system operators to analyze the events in real time due to their high reporting rates. Real-time detection and classification of the fault related events as no-fault, fault-incidence, fault-on and post-fault stage with no further disturbance, is an important requirement in order to decide on the control actions to protect the system from any instability. In this paper, a sliding window based continuous online monitoring method of the power system using convolutional neural networks is proposed. The effectiveness of the proposed method is validated on the 127-bus Western Systems Coordinating Council test system.",

keywords = "Classification, deep learning, online monitoring, power system monitoring",

author = "Mert Kesici and Saner, {Can Berk} and Mohammed Mahdi and Yusuf Yaslan and Genc, {V. M.Istemihan}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 ; Conference date: 25-04-2019 Through 26-04-2019",

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series = "7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings",

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

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Kesici, M, Saner, CB, Mahdi, M, Yaslan, Y & Genc, VMI 2019, Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks. in A Cetin (ed.), 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings., 8782365, 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 223-227, 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019, Istanbul, Turkey, 25/04/19. https://doi.org/10.1109/SGCF.2019.8782365

Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks. / Kesici, Mert; Saner, Can Berk; Mahdi, Mohammed et al.
7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings. ed. / Aydin Cetin. Institute of Electrical and Electronics Engineers Inc., 2019. p. 223-227 8782365 (7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings).

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

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AB - Online monitoring of the power system is a vital application for enhancing the situational awareness capabilities of the system. Rapid integration of phasor measurement units in the network enables transmission system operators to analyze the events in real time due to their high reporting rates. Real-time detection and classification of the fault related events as no-fault, fault-incidence, fault-on and post-fault stage with no further disturbance, is an important requirement in order to decide on the control actions to protect the system from any instability. In this paper, a sliding window based continuous online monitoring method of the power system using convolutional neural networks is proposed. The effectiveness of the proposed method is validated on the 127-bus Western Systems Coordinating Council test system.

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Kesici M, Saner CB, Mahdi M, Yaslan Y , Genc VMI. Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks. In Cetin A, editor, 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 223-227. 8782365. (7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings). doi: 10.1109/SGCF.2019.8782365

Wide Area Measurement Based Online Monitoring and Event Detection Using Convolutional Neural Networks

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

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