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Partial Y-Bus Factorization Algorithm for Power System Dynamic Equivalents

Author

Listed:
  • Soobae Kim

    (Department of Electrical Engineering, School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea)

  • Thomas J. Overbye

    (Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA)

Abstract

This paper presents a partial Y-bus factorization algorithm to reduce the size of a power system model for transient stability analysis. In the proposed approach, steady-state operating conditions for dynamic equivalents are maintained using the traditional Ward admittance method. Fictitious generators are attached at boundary buses to preserve transient behavior following a disturbance. The equivalent dynamic effects from eliminated generators can be maintained by choosing appropriate dynamic parameters of fictitious generators, including machine inertia, transient reactance, and the damping coefficient. Parameters are determined using the idea that the contributions from external generators mostly depend on the network configuration and impedance characterized by the Y-bus matrix. The fictitious generators’ dynamic parameters are determined by conducting partial Y-bus factorization on dynamic parameter matrices. The proposed method’s performance is validated by conducting case studies with the IEEE 118-bus system and a 10,000 synthetic western U.S. power grid model and comparing simulation outcomes between the full system and reduced equivalent models. Simulation comparisons show that the equivalent model maintains high accuracy. The proposed method is promising alternative solution for power system dynamic equivalents.

Suggested Citation

  • Soobae Kim & Thomas J. Overbye, 2022. "Partial Y-Bus Factorization Algorithm for Power System Dynamic Equivalents," Energies, MDPI, vol. 15(3), pages 1-10, January.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:682-:d:727280
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    Cited by:

    1. Mengjun Liao & Lin Zhu & Yonghao Hu & Yang Liu & Yue Wu & Leke Chen, 2023. "Dynamic Equivalent Modeling of a Large Renewable Power Plant Using a Data-Driven Degree of Similarity Method," Energies, MDPI, vol. 16(19), pages 1-20, October.

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