Power-System Ambient-Mode Estimation Considering Spectral Load Properties

Existing mode meter algorithms were derived with the assumption that load variations are accurately represented by white noise or an integral of white noise, which may not be satisfied in actual power systems. This paper proposes a mode meter algorithm which relaxes this assumption by explicitly taking into account spectral load characteristics. These characteristics can be either measured or estimated using the inverse of the existing power system model. The method is developed assuming an autoregressive moving average (ARMA) model of the system and incorporating estimated correlations between loads as inputs and synchrophasor measurements as outputs. Performances of the proposed method are compared with the Yule-Walker and N4SID methods using simulated synchrophasor data obtained from the KTH Nordic 32 test system. Finally, the effects of measurement noise on the proposed method are analyzed, as well as the effects of model uncertainty when the power system model is used to determine spectral load characteristics. It is shown that the proposed algorithm increases accuracy in mode estimates when the loads are described with nonwhite noise.