Identification of multiple harmonic sources in power system containing inverter‐based distribution generations using empirical mode decomposition

Abstract

This paper proposes an identification method of multiple harmonic sources in the presence of different inverter-based distributed generations (DG) such as photovoltaic (PV), wind turbine with doubly fed induction generator (DFIG), and microturbine (MT) at the point of common coupling (PCC). To classify the linear loads, non-linear loads (NL) and inverter-based DGs, K-nearest neighbours (KNN) classifier was employed. The features were extracted using empirical mode decomposition (EMD), just from voltage waveforms. To reduce the redundant data, dimension of features vector, and time, the Relief-F method was implemented on the extracted features. Utilising only the voltage waveform for extraction of features increases the speed of the process and decreases the number of measurement equipment. To verify the effectiveness of the proposed method, a number of scenarios such as different harmonic sources with various harmonic orders, load and DG levels were simulated. The results on two test systems showed that the proposed method has a high accuracy even in the presence of different inverter-based DGs. It can be used as an added tool for power-quality engineers and can be integrated into monitor instruments. Also, the speed and precision of this method make it suitable for real-time applications in the power-quality issues.