Frequency-Coupled Admittance Modeling Of Converter-Interfaced Generators Using Linear Regression

Oscillation is becoming one of the most critical issue in a power system with large-scale renewable integration. Frequency-coupled admittance model (FCAM) is widely used in the analysis of oscillations. The operating conditions of converter-interfaced generators (CIGs) are variable in the evaluation of oscillation risk. Therefore, it is necessary to construct the functions of FCAM on the operating conditions. However, the existing modeling methods for FCAM has not taken variable conditions into account. The state-space modeling method is unable to establish accurate models for CIGs with unknown structures and parameters. The impedance measurement method can only obtain the impedance under a specific operating condition once at a time. Moreover, the measured model cannot represent the dynamics under other operating situations. To fill this gap, a linear regression-based modeling method is proposed in this paper. The FCAMs of the CIG are measured under several operating conditions. Linear regression is then used to obtain FCAM as a function of operating conditions. The effectiveness and accuracy of the proposed method is verified by comparing the theoretical model and the regression model.