Power System Control & Protection Lab

Synchrophasor Systems

Paper In Journals

  1. M. Alqudah, M. Kezunovic, Z. Obradovic, “Automated Power System Fault Prediction and Precursor Discovery Using Multi-modal Data” in IEEE Access, vol. 11, pp. 7283-7296, December 2022, doi: 10.1109/ACCESS.2022.3233219
  2. M. Alqudah, M. Pavlovski, T. Dokic, M. Kezunovic, Y. Hu, Z. Obradovic, “Convolution-based Fault Detection Utilizing Timeseries Synchrophasor Data from Phasor Measurement Units,” in IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3434-3442, September 2022, DOI:  10.1109/TPWRS.2021.3135336
  3. M. Pavlovski, M. Alqudah, T. Dokic, A. Abdel Hai, M. Kezunovic, Z. Obradovic, “ Hierarchical Convolutional Neural Networks for Event Classification on PMU Data,” in IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-13, 2021, Art no. 2514813, September 2021, DOI: 10.1109/TIM.2021.3115583
  4. A. Abdel Hai, T. Dokic, M. Pavlovski, T. Mohamed, D. Saranovic, M. Alqudah, M. Kezunovic, Z. Obradovic, “Transfer Learning for Event Detection from PMU Measurements with Scarce Labels” in IEEE Access, Vol. 9, pp. 127420 – 127432, 10 September 2021, DOI: 10.1109/ACCESS.2021.3111727.
  5. M. Kezunovic, P. Pinson, Z. Obradovic, S. Grijalva, T. Hong, and R. Bessa, “Big Data Analytics for Future Electricity Grids,” Electric Power Systems Research, Vol. 189, No., pp. 106788, 2020, DOI: 10.1016/j.epsr.2020.106788.
  6. C. Qian and M. Kezunovic, “A Power Waveform Classification Method for Adaptive Synchrophasor Estimation,” in IEEE Transactions on Instrumentation and Measurement, Vol. 67, No. 7, pp.1646-1658, July 2018.

Papers In Proceedings of Refereed Conferences

  1. H. Otudi, T. Mohamed, M. Kezunovic, Y. Hu, Z. Obradovic, “Training Machine Learning Models with Simulated Data for Improved Line Fault Events Classification From 3-Phase PMU Field Recordings,” The Hawaii International Conference on System Sciences (HICSS-56), Hawaii, USA, January 2023.
  2. A. Abdel Hai, T. Mohamed, M. Pavlovski, M. Kezunovic, Z. Obradovic, “Transfer Learning on Phasor Measurement Data from a Power System to Detect Events in Another System”, in 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), Bahamas, December 2022.
  3. T. Mohamed, M. Kezunovic, Z. Obradovic, Y. Hu and Z. Cheng, “Application of Machine Learning to Oscillation Detection using PMU Data based on Prony Analysis,” 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Novi Sad, Serbia, 2022, pp. 1-5, doi: 10.1109/ISGT-Europe54678.2022.9960589.
  4. M. Kezunovic, Z. Obradovic, Y. HU, “Use of Machine Learning on PMU Data for Transmission System Fault Analysis,” CIGRE General Session, Paper # 191, Paris, France, August 2022.
  5. M. Kezunovic, Z. Obradovic, Y. Hu, “Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data,” CIGRE General Session, Paper # 224, Paris, France, August 2022.
  6. T. Mohamed, M. Kezunovic, J. Lusher, J. C. Liu, J. Ren, “The Use of Digital twin for Timing Intrusion Detection in Synchrophasor Systems,” IEEE Power and Energy General Meeting, Denver, Colorado, July 2022.
  7. T. Dokic, R. Baembitov, A. A. Hai, Z. Cheng, Y. Hu, M. Kezunovic and Z. Obradovic., “Machine Learning Using a Simple Feature for Detecting Multiple Types of Events from PMU Data,” in 2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), 24-26 May 2022 2022, pp. 1-6, doi: 10.1109/SGSMA51733.2022.9806000.
  8. Z. Cheng, Y.  Hu , Z. Obradovic , M. Kezunovic, “Using Synchrophasor Status Word as Data Quality Indicator: What to Expect in the Field?” 2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), 24-26 May 2022 2022, doi: 10.1109/SGSMA51733.2022.9806010.
  9. H. Otudi, T. Dokic, T. Mohamed, M. Kezunovic, Y. Hu, Z. Obradovic, “Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements,” HICSS-55 Conference, Hawaii, USA, January 2022, DOI: 10.24251/HICSS.2022.425.
  10. R. Baembitov, T. Dokic, M. Kezunovic and Z. Obradovic,  “Fast Extraction and Characterization of Fundamental Frequency Events from a Large PMU Dataset Using Big Data Analytics,” HICSS-54 Conference, Hawaii, USA, January 2021, DOI: 10.24251/HICSS.2021.389.
  11. K. Panda, A. Mohapatra, S. C. Srivastava and M. Kezunovic, “Energy Function Based Approach for Online Inertia Estimation Utilizing Synchrophasor Measurements,” 2020 IEEE Texas Power and Energy Conference (TPEC), College Station, TX, 2020, DOI: 10.1109/TPEC48276.2020.9042566.
  12. M. Kezunovic, T. Dokic, Z. Obradovic, M. Pavlovski, R. Said “Big Data Analytics for Predictive Lightning Outage Management Using Spatially Aware Logistic Regression Model”, CIGRE General Session, Aug. 2020, Paris, France. (online)
  13. M. Kezunovic, P. Pinson, Z. Obradovic,  S. Grijalva, T. Hong, R. Bessa, “Big Data Analytics for Future Electricity Grids”, Power Systems Computation Conference, Porto, Portugal, July, 2020 (online), DOI: 10.1016/j.epsr.2020.106788.
  14. C. Seidl, and M. Kezunovic, “Tools for End-to-end Analysis, Calibration and Troubleshooting of Synchrophasor Systems,” ISGT Europe 2019, Bucharest, Romania, September 2019.
  15. C. Qian, M. Kezunovic, “Power System Fundamental Frequency Estimation Using Unscented Kalman Filter,” IEEE PES General Meeting, Atlanta, Georgia, August, 2019.
  16. M. Kezunovic, C. Qian, C. Seidl, J. Ren., “Testbed for Timing Intrusion Evaluation and Tools for Lab and Field Testing of Synchrophasor System,” The First IEEE International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), College Station, TX. May 2019.
  17. C. Qian, M. Kezunovic, “Hybridization Framework for Improved Dynamic Phasor Parameter Estimation Algorithms,” 2019 IEEE PES Conference on Innovative Smart Grid Technologies North America (ISGT NA 2019), Washington, D.C., USA, February 2019

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