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Spatial Characterization of Sub-Synchronous Oscillations Using Black-Box IBR Models

Muhammad Sharjeel Javaid, Gabriel Covarrubias Maureira, Ambuj Gupta, Debraj Bhattacharjee, Jianli Gao, Balarko Chaudhuri, Mark O'Malley

Abstract

Power systems with high penetration of inverter-based resources (IBRs) are prone to sub-synchronous oscillations (SSO). The opaqueness of vendor-specific IBR models limits the ability to predict the severity and the spread of SSO. This paper demonstrates that black-box IBR models estimated through frequency-domain identification techniques, along with dynamic network model can replicate the actual oscillatory behavior. The estimated IBR models are validated against actual IBR models in a closed-loop multi-IBR test system through modal analysis by comparing closed-loop eigenvalues, and participation factors. Furthermore, using output-observable right eigenvectors, spatial heatmaps are developed to visualize the spread and severity of dominant SSO modes. The case studies on the 11-bus and 39-bus test systems confirm that even with the estimated IBR models, the regions susceptible to SSO can be identified in IBR-dominated power systems.

Spatial Characterization of Sub-Synchronous Oscillations Using Black-Box IBR Models

Abstract

Power systems with high penetration of inverter-based resources (IBRs) are prone to sub-synchronous oscillations (SSO). The opaqueness of vendor-specific IBR models limits the ability to predict the severity and the spread of SSO. This paper demonstrates that black-box IBR models estimated through frequency-domain identification techniques, along with dynamic network model can replicate the actual oscillatory behavior. The estimated IBR models are validated against actual IBR models in a closed-loop multi-IBR test system through modal analysis by comparing closed-loop eigenvalues, and participation factors. Furthermore, using output-observable right eigenvectors, spatial heatmaps are developed to visualize the spread and severity of dominant SSO modes. The case studies on the 11-bus and 39-bus test systems confirm that even with the estimated IBR models, the regions susceptible to SSO can be identified in IBR-dominated power systems.
Paper Structure (8 sections, 7 equations, 9 figures, 1 table)

This paper contains 8 sections, 7 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. IBR Model Estimation Techniques
  3. Modal Analysis Overview
  4. System-wide Observability of Oscillation
  5. IBR Participation Factor
  6. Validity of Estimation Technique
  7. Application on 39-Bus Test System
  8. Conclusion

Figures (9)

  • Figure 1: Power system modeling with estimated IBR admittance transfer functions.
  • Figure 2: Kundur 11-bus test system with three GFLs and one GFM kundur1994power.
  • Figure 3: SSO observed in voltage magnitude of all four IBRs when power injection from IBR2 is increased by 5% (from 5.2 pu to 5.46 pu).
  • Figure 4: Sub-synchronous eigenvalues $\lambda_\textrm{SSO}$ of the model-based closed-loop 11-bus test system (left). Normalized participation of IBRs $\tilde{\mathcal{P}}_\textrm{IBR}$ in the least damped SSO $\lambda_{\textrm{SSO}_1}$ (right).
  • Figure 5: Comparison of singular values of estimated admittance transfer function with the singular values of actual model admittance of all four IBRs.
  • ...and 4 more figures