An Improved Interpolated DFT-Based Parameter Identification for Sub-/Super-Synchronous Oscillations With Synchrophasors

The sub-synchronous resonance oscillations (SSO) caused by considerable renewable energy generations and power electronic devices seriously affect power system stability. Synchrophasor-based SSO parameter identification can effectively monitor SSOs. Aiming at the fundamental and frequency-coupled sub-/super-synchronous components that appear simultaneously in SSOs, an improved parameter identification algorithm is proposed in this paper based on the original interpolation Discrete Fourier Transform (DFT) and Hann-window. As the complement to the original algorithm, the improvements proposed in this paper additionally focus on the influence between the positive-/negative-frequency parts of the sub-/super-synchronous and fundamental components. Thus, the frequency, amplitude, and phase of the fundamental, sub-synchronous, and super-synchronous components can be accurately obtained by the proposed algorithm. This algorithm is compared to the original interpolated DFT and Prony analysis with both the simulated Phasor Measurement Unit (PMU) data and PMU data recorded during an actual SSO incident to verify its correctness and effectiveness. In the improved algorithm, the additional consideration for the super-synchronous component and the additional identified parameters significantly enhance the practical value of the interpolated DFT algorithm.

I. Introduction

In modern power systems, sub-synchronous oscillations (SSO) or sub-synchronous resonance (SSR) are mainly caused by resonances between power electronic devices and compensators [1]–[3] or weak transmission lines [4], [5]. Compared with the SSOs caused by the torsional vibration of traditional steam turbine shaft systems, the resonance mechanism of SSO caused by power electronic devices is more complicated, and the oscillation characteristics are more variable, which in turn has a severe impact on power systems. These SSOs will significantly limit the power generation of renewable energy or even cause system instability. Therefore, it is necessary to accurately identify the parameters of the voltage and current instantaneous signals during SSOs to monitor the occurrence and spreading of SSOs effectively [6], thereby mitigating SSOs [7]–[9]. Early studies have shown that SSOs can be monitored based on synchrophasors, and the frequency of sub-synchronous oscillations can be identified [10], [11]. However, since synchrophasors can only provide synchronized fundamental phasors rather than instantaneous signals, it is difficult to identify other sub-synchronous parameters based on synchrophasors, e.g., the amplitudes and phases [10], [12], [13].