Data analytics applications to fault locations and overcurrent protection devices

Power quality (PQ) monitors installed in transmission and distribution systems record disturbance events occurring in the system, such as root mean square (RMS) variations and transients caused by short-circuit faults, transformer energizing, or capacitor switching around the clock, resulting in a large amount of data. Although the collected data contain valuable information about the system, they are often merely stored without any further analysis. Analysis of these data presents opportunities for improving the performance of power systems as well as for monitoring the health of the grid as a whole. The general objective of this proposal is to develop algorithms that make use of three phase voltage and current measurements recorded from the power quality monitors. Specifically, algorithms are developed for the analysis of (1) short circuit faults with their locations (fault analytics) and (2) overcurrent protection devices installed in the system (device analytics). The fault analytics module is used to identify fault events among other power quality events and estimates the location to the fault occurring in the system. The proposed method uses variable window size in calculating phasors and estimates a single fault location that is more accurate than the multiple locations estimated by the conventional approach using Fourier and cosine filters. The device analytics module aims to evaluate the overcurrent protection devices operating to isolate short-circuit faults from the system. This module identifies recloser and fuse operations and estimates the empirical inverse time-current characteristics of the devices. The results of the device analytics are used to evaluate device opening intervals and coordination and to further narrow down fault location because faults are located downstream from the clearing device. Finally, the dissertation presents a data analytics framework and an open power quality disturbance event schema. The schema is developed to promote the sharing of data recording PQ disturbance events and the metadata providing descriptive and quantitative analysis of the events.