Power quality event dynamics characterization via 2D trajectories using deviations of higher-order statistics

This paper presents a measurement procedure to be implemented in smart Power Quality Analyzers (PQA), and conceived to monitor service nodes in the current electrical network. It is thought on the need for developing measurement instruments capable of detecting newly PQ events, which commonly appear in the modern Smart Grid (SG), adding at the same time complementary information, regarding the real-time network state, than the conventional meters do. Its novelty resides in the deployment of the events' trajectories in three types of 2D maps based in Higher-Order Statistics (HOS). The events under study appear isolated or in hybrid versions: sags and transients. Examining the HOS dynamics (trajectories in the HOS planes), the procedure allows the online detection and help detect specific types of events. Additionally, this trajectory-based method reveals some other features like hybrid events, the depth or event degree, the duration and the phase changes. The results are based on real-life signals, which have been surveyed in a building's node. A complementary deviation index gathers the information regarding the individual distances between each statistic and its associated ideal value.