A composite power quality disturbance detection method based on extremum extension optimized SVMD and Teager Energy Operator

Abstract The growth of nonlinear loads and distributed generation in power grids has increased the frequency and complexity of power quality disturbances (PQDs). To improve PQ, it is necessary to accurately detect disturbance parameters, identify the causes of disturbances, and formulate corresponding management measures. Traditional disturbance detection methods primarily target single disturbances. As a contribution to complex disturbances, this paper proposes a composite PQD detection method based on extremum extension successive variational mode decomposition and Teager Energy Operator (EE-SVMD-TEO). Briefly, the SVMD method is utilized to decompose PQD signals. This method is further improved using an EE approach to reduce the influence of endpoint effects. Subsequently, the TEO is applied to the disturbance components obtained from the SVMD for disturbance detection. The results from composite disturbance detection simulation experiments show that the proposed method can differentiate disturbances in composite PQD signals. Combined with TEO, it successfully recognizes the start and end times of each disturbance, achieving a detection accuracy of over 97.5% at a signal-to-noise ratio of 30 dB Gaussian white noise. By comparing the modal decomposition results, the detection accuracy of disturbance time points, and the detection result stability, our method is more suitable for detecting composite PQD events than EEMD-TEO and EWT-TEO.