A novel adaptive linear prediction-based parameter estimation method for monitoring sub-/inter-harmonics during SSI events

Abstract

Sub-Synchronous Interaction (SSI), caused by the increasing penetration of inverter connected nonsynchronous generation, is posing a serious threat on power system stability. As the sub-/inter-harmonics emerging during SSI are featured by time-varying frequencies, concerns regarding the accuracy and the robustness of existing methods for monitoring oscillations of such phenomenon have been raised. This paper proposes a novel two-stage numerical method for monitoring the sub-harmonics, harmonics and inter-harmonics during SSI events. In the first stage, the model order of the estimation is selected using the proposed Adaptive Model Order Selection (AMOS) scheme, which is achieved through singular value decomposition. In the second stage, a linear prediction-based parameter estimation approach with high accuracy and strong robustness is used to estimate the signal parameters of the sub-harmonics, harmonics and inter-harmonics. By merging the above two stages, a novel and effective numerical method is obtained, namely the Adaptive Linear Prediction-based Parameter Estimation (ALPPE) method. In addition, an estimation calibration is implemented to increase the estimation accuracy. The proposed ALPPE method has then been tested using computer simulated signals and field measured data from an actual SSI event. The results of the tests confirmed the ALPPE method's high accuracy, adaptability, processing speed and immunity to noise.