PMU analytics for power fault awareness and prediction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The analysis of electrical wave measurements on an electricity grid obtained through Phasor Measurement Units (PMUs) offers a unique opportunity to detect power system faults in real time. The goal of this study is to evaluate the use of classification and forecasting models to recognize and predict power system faults in streaming PMU data. The evaluation of these models built with simulated PMU data from a real-world power network demonstrates that both classification and forecasting can be successfully used in the detection and prediction of single line and three phase to ground faults. The results obtained indicate that the same methodology can be applied to other types of power system faults.

Original languageEnglish
Title of host publication2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728116075
DOIs
Publication statusPublished - 1 May 2019
Event2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019 - College Station, United States
Duration: 20 May 201923 May 2019

Publication series

Name2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019

Conference

Conference2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019
CountryUnited States
CityCollege Station
Period20/5/1923/5/19

Fingerprint

Phasor measurement units
Fault
Power System
Unit
Prediction
predictions
forecasting
Forecasting
Electricity
electricity
Streaming
grids
methodology
Grid
Predict
Awareness
Methodology
evaluation
Evaluate
Line

Keywords

  • Current measurement
  • Electrical fault detection
  • Phasor measurement units
  • Power system fault
  • Voltage measurement

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Numerical Analysis
  • Instrumentation

Cite this

Wanik, M. Z. B. C., Sanfilippo, A., Singh, N., Jabbar, A., & Cen, Z. (2019). PMU analytics for power fault awareness and prediction. In 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019 [8784461] (2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SGSMA.2019.8784461

PMU analytics for power fault awareness and prediction. / Wanik, Mohd Z. Bin Che; Sanfilippo, Antonio; Singh, Nand; Jabbar, Abdullah; Cen, Zhaohui.

2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8784461 (2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wanik, MZBC, Sanfilippo, A, Singh, N, Jabbar, A & Cen, Z 2019, PMU analytics for power fault awareness and prediction. in 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019., 8784461, 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019, Institute of Electrical and Electronics Engineers Inc., 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019, College Station, United States, 20/5/19. https://doi.org/10.1109/SGSMA.2019.8784461
Wanik MZBC, Sanfilippo A, Singh N, Jabbar A, Cen Z. PMU analytics for power fault awareness and prediction. In 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8784461. (2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019). https://doi.org/10.1109/SGSMA.2019.8784461
Wanik, Mohd Z. Bin Che ; Sanfilippo, Antonio ; Singh, Nand ; Jabbar, Abdullah ; Cen, Zhaohui. / PMU analytics for power fault awareness and prediction. 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019).
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