A Two-stage Fault Location Identification Method in Multi-area Power Grids Using Heterogeneous Types of Data

This paper proposes a two-stage fault location method for multiarea power systems. It utilizes available heterogeneous types of data consisting of status data (i.e., discrete data) and analog data (i.e., continues data). A distributed casual model-based diagnosis method using P-invariant Petri nets is proposed that utilizes status data to find faulted sections. Each subsystem/area of multiarea power systems has its own diagnostic model and determines the diagnosis solution based on its local net, the local manifestations, and limited information exchange with the neighboring subsystems/areas. Once a short list of possible fault sections is determined, the second stage further improves the estimated fault location using analog data. The actual fault location is estimated by comparing the measured analog data with their associated calculated values in computer programs using short-circuit analysis algorithms. Simulation results demonstrate that the proposed distributed fault location method can diagnose faults in multiarea power systems accurately.