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Ultrafast Grid Impedance Identification in $dq$-Asymmetric Three-Phase Power Systems

Mohamed Abdalmoaty, Verena Häberle, Xiuqiang He, Florian Dörfler

Abstract

We propose a non-parametric frequency-domain method to identify small-signal $dq$-asymmetric grid impedances, over a wide frequency band, using grid-connected converters. Existing identification methods are faced with significant trade-offs: e.g., passive approaches rely on ambient harmonics and rare grid events and thus can only provide estimates at a few frequencies, while many active approaches that intentionally perturb grid operation require long time series measurement and specialized equipment. Although active time-domain methods reduce the measurement time, they either make crude simplifying assumptions or require laborious model order tuning. Our approach effectively addresses these challenges: it does not require specialized excitation signals or hardware and achieves ultrafast ($<1$ s) identification, drastically reducing measurement time. Being non-parametric, our approach also makes no assumptions on the grid structure. A detailed electromagnetic transient simulation is used to validate the method and demonstrate its clear superiority over existing alternatives.

Ultrafast Grid Impedance Identification in $dq$-Asymmetric Three-Phase Power Systems

Abstract

We propose a non-parametric frequency-domain method to identify small-signal -asymmetric grid impedances, over a wide frequency band, using grid-connected converters. Existing identification methods are faced with significant trade-offs: e.g., passive approaches rely on ambient harmonics and rare grid events and thus can only provide estimates at a few frequencies, while many active approaches that intentionally perturb grid operation require long time series measurement and specialized equipment. Although active time-domain methods reduce the measurement time, they either make crude simplifying assumptions or require laborious model order tuning. Our approach effectively addresses these challenges: it does not require specialized excitation signals or hardware and achieves ultrafast ( s) identification, drastically reducing measurement time. Being non-parametric, our approach also makes no assumptions on the grid structure. A detailed electromagnetic transient simulation is used to validate the method and demonstrate its clear superiority over existing alternatives.
Paper Structure (20 sections, 29 equations, 6 figures, 3 tables)

This paper contains 20 sections, 29 equations, 6 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Problem formulation
  3. Small-signal model
  4. Grid-connected converter
  5. Measurement setup
  6. Grid Impedance Identification
  7. Relation between voltage and current DFT spectra
  8. Local parametric modeling
  9. Special cases
  10. The periodic excitation case
  11. The dq-symmetric grid case
  12. The periodic excitation and dq-symmetric grid case
  13. Extracting the four real TFs
  14. Numerical simulation study
  15. Experiment Setup
  16. ...and 5 more sections

Figures (6)

  • Figure 1: Grid-connected converter system with excitation in the control loop.
  • Figure 2: Measurement setup. Voltage and current noise represent errors due to inaccuracies of the measurement devices $S_i$ and $S_v$. Grid disturbances represent possible ambient harmonics and/or transient events in the grid. The natural converter's switching harmonics act as an additional excitation signal.
  • Figure 3: One-line diagram of the three-phase grid used in the simulation.
  • Figure 4: Magnitude frequency response of the true equivalent impedance $Z_g(s)$
  • Figure 5: Error magnitude $|\hat{Z}_{dd}(j\omega) - Z_{dd}(j\omega)|, \; |\hat{Z}_{dq}(j\omega) - Z_{dq}(j\omega)|$ in case of noise corrupted measurements. The errors of $\hat{Z}_{qd}(j\omega)$ and $\hat{Z}_{qq}(j\omega)$ (not shown) exhibit the same behavior. The magnitude of the true responses (dashed gray) are overlaid to highlight the location of the resonances.
  • ...and 1 more figures