Exploratory data analysis to evaluate the propagation of disturbances originating in a short circuit

As a consequence of a short circuit in the power electrical system, there is a power quality disturbance occurring in the voltage/current signal that is propagated along the bars that compose the system with different characteristics and it is influenced by several factors, which makes it difficult to develop methods that can be used to locate the fault. Considering the advanced measurement infrastructure originating from the smart grid, these signals can be measured in real time and analyzed in a control and operation center improving the reliability of the system. This paper performs an exploratory data analysis on a database of voltage signals during the occurrence of a short circuit applied to the IEEE 34Bus system, aimed at the discovery of heuristics that can assist in decision making. The database includes information from voltage signals measured at each bar of the system and was assembled from simulations of three-phase, two-phase, and single-phase short circuits. Statistical metrics and data visualization are applied on the data subset to infer how the disturbance propagation occurs according to characteristics that are extracted from the measured signal during the presence of a fault in the power distribution system. This work shows that the combination of graphical, statistical modeling techniques is a powerful approach to explore these events. Multivariate data analysis has benefits over classical approaches that are based on raw data.