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An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data

Author

Listed:
  • Moossa Khodadadi Arpanahi

    (Department of Electrical and Computer Engineering, Isfahan University of Technology (IUT), Isfahan 84156-83111, Iran)

  • Meysam Kordi

    (Intelliwide Company, Ergonomic and Capable Products for Power Systems, Isfahan 8173986561, Iran)

  • Roozbeh Torkzadeh

    (Institute of Science and Technology, Universidad Loyola Andalucía, Campus de Palmas Altas, No. 1, Energy Solar St., 41014 Seville, Spain)

  • Hassan Haes Alhelou

    (Department of Electrical and Computer Engineering, Isfahan University of Technology (IUT), Isfahan 84156-83111, Iran
    Department of Electrical Power Engineering, Faculty of Mechanical and Electrical Engineering, Tishreen University, Lattakia 2230, Syria)

  • Pierluigi Siano

    (Department of Management & Innovation Systems, University of Salerno, 84084 Salerno, Italy)

Abstract

Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and are mainly calculated using Hilbert–Huang transform (HHT) methods. Those methods, however, suffer from the end effects, mode-mixing and Gibbs phenomena since they use an iterative procedure. This paper proposes an augmented Prony method for power system oscillation analysis using synchrophasor data obtained from a wide-area measurement system (WAMS). In the proposed method, in addition to the estimation of the modal information, IMFs are extracted using a new explicit mathematical formulation. Further, an indicator based on an energy and phase relationship of IMFs is proposed, which allows system operators to recognize the most effective generators/actuators on specific modes. The method is employed as an online oscillation-monitoring framework providing inputs for the so-called wide-area damping control (WADC) module. The efficacy of the proposed method is validated using three test cases, in which the IMFs calculation is simpler and more accurate if compared with other methods.

Suggested Citation

  • Moossa Khodadadi Arpanahi & Meysam Kordi & Roozbeh Torkzadeh & Hassan Haes Alhelou & Pierluigi Siano, 2019. "An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data," Energies, MDPI, vol. 12(7), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1267-:d:219213
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    Cited by:

    1. Pierluigi Siano & Miadreza Shafie-khah, 2020. "Special Issue on Advanced Approaches, Business Models, and Novel Techniques for Management and Control of Smart Grids," Energies, MDPI, vol. 13(11), pages 1-3, May.

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