SVM-Based Parameter Identification for Composite ZIP and Electronic Load Modeling

This paper proposes a parameter identification technique for composite ZIP and electronic loads by leveraging the support vector machine (SVM) approach. Since the active power and the reactive power of electronic loads are piecewise functions of the voltage magnitude, the operating modes of electronic loads are determined by the voltage magnitude. To improve the accuracy of parameter identification, two filters (Hampel and Savitzky–Golay) are employed to preprocess measurements to reduce noise. The data after noise reduction serve as training data for the regression model that is solved by the SVM approach. Numerical results show that the SVM approach with filters can identify the parameters of the composite ZIP and electronic load model with high accuracy.