Homology detection method for voltage sags based on space vector and maximum mean discrepancy

Abstract

A single voltage sag source may trigger multiple power quality monitors to record waveforms resulting in the redundancy of voltage sag monitoring data. To address this problem, a homology detection method for voltage sags based on a space vector and maximum mean discrepancy was proposed, which is conducive for locating accurate voltage sag sources and inverting sag event propagation paths. First, a waveform transformation method based on a space vector was proposed to eliminate the influence of the transformer on voltage sag propagation. Second, a two-sample test method for voltage sags based on the maximum mean discrepancy was proposed to detect whether any two voltage sag waveforms are caused by the same voltage sag source. The connected graph method was used to identify the number of sag sources; this avoids the difficulty in accurately selecting the number of clusters. The measured and simulation data of the IEEE 30-bus system were used for verification, and the results verified the correctness and effectiveness of the proposed method. The proposed method can be implemented in a power quality monitoring system as a pre-processing step to support related research activities.

Keywords

• Voltage sags
• Homology detection
• Space vector
• Maximum mean discrepancy
• Bootstrap method