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Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue. / Bhandia, Rishabh; Cvetkovic, Milos; Chavez Muro, Jose; Palensky, Peter.

Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy. IET, 2019.

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Harvard

Bhandia, R, Cvetkovic, M, Chavez Muro, J & Palensky, P 2019, Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue. in Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy. IET, 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, Dubrovnik, Croatia, 12/11/18. https://doi.org/10.1049/cp.2018.1877

APA

Bhandia, R., Cvetkovic, M., Chavez Muro, J., & Palensky, P. (2019). Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue. In Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy IET. https://doi.org/10.1049/cp.2018.1877

Vancouver

Bhandia R, Cvetkovic M, Chavez Muro J, Palensky P. Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue. In Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy. IET. 2019 https://doi.org/10.1049/cp.2018.1877

Author

Bhandia, Rishabh ; Cvetkovic, Milos ; Chavez Muro, Jose ; Palensky, Peter. / Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue. Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy. IET, 2019.

BibTeX

@inproceedings{bff21ee3c77b4ff7a90571347ca30602,
title = "Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue",
abstract = "The key contributor to normal power grid operations are optimal working of the various power grid equipment/apparatus. Non-optimal operation of any of these equipment causes power quality problems which can pose great risk to the stability of the grid. A damaged or partially damaged equipment leaves characteristic signatures in the form of current and voltage waveform distortions. Detecting and localizing such signal distortions would contribute to grid reliability as the damaged equipment could be replaced in time before it can cause further damage. This paper proposes a Distortion Detection Technique (DDT) based on second-difference approach. This distortion detection technique has very low memory requirements and can be easily implemented on decentralized systems. The paper investigates the performance of this technique and evaluates it with case studies involving different kind of equipment failures simulated on Real Time Digital Simulator (RTDS).",
author = "Rishabh Bhandia and Milos Cvetkovic and {Chavez Muro}, Jose and Peter Palensky",
year = "2019",
doi = "10.1049/cp.2018.1877",
language = "English",
booktitle = "Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy",
publisher = "IET",

}

RIS

TY - GEN

T1 - Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue

AU - Bhandia, Rishabh

AU - Cvetkovic, Milos

AU - Chavez Muro, Jose

AU - Palensky, Peter

PY - 2019

Y1 - 2019

N2 - The key contributor to normal power grid operations are optimal working of the various power grid equipment/apparatus. Non-optimal operation of any of these equipment causes power quality problems which can pose great risk to the stability of the grid. A damaged or partially damaged equipment leaves characteristic signatures in the form of current and voltage waveform distortions. Detecting and localizing such signal distortions would contribute to grid reliability as the damaged equipment could be replaced in time before it can cause further damage. This paper proposes a Distortion Detection Technique (DDT) based on second-difference approach. This distortion detection technique has very low memory requirements and can be easily implemented on decentralized systems. The paper investigates the performance of this technique and evaluates it with case studies involving different kind of equipment failures simulated on Real Time Digital Simulator (RTDS).

AB - The key contributor to normal power grid operations are optimal working of the various power grid equipment/apparatus. Non-optimal operation of any of these equipment causes power quality problems which can pose great risk to the stability of the grid. A damaged or partially damaged equipment leaves characteristic signatures in the form of current and voltage waveform distortions. Detecting and localizing such signal distortions would contribute to grid reliability as the damaged equipment could be replaced in time before it can cause further damage. This paper proposes a Distortion Detection Technique (DDT) based on second-difference approach. This distortion detection technique has very low memory requirements and can be easily implemented on decentralized systems. The paper investigates the performance of this technique and evaluates it with case studies involving different kind of equipment failures simulated on Real Time Digital Simulator (RTDS).

U2 - 10.1049/cp.2018.1877

DO - 10.1049/cp.2018.1877

M3 - Conference contribution

BT - Proceedings of 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy

PB - IET

ER -

ID: 47450232