UAV-Assisted Fault Location Coordinated Strategy for Resilient Distribution Systems

Abstract

The orderly and rapid restoration of the distribution system (DS) after disasters depends on the accuracy and reliability of fault location. Disasters may also damage the communication infrastructure, resulting in untimely reporting of fault information detected by remote fault indicators (RFIs). In this paper, we propose an unmanned aerial vehicle (UAV) assisted coordination strategy for status collection and fault location in distribution systems. The strategy utilizes the RFIs’ fault status indication information collected by UAVs in the communication fault area for fault location. A co-optimization model for information acquisition and fault location is established, taking into account the probability of possible fault scenarios, the total amount of status information collected, and the working time of UAVs for multiple objectives. The model is transformed into a mixed-integer second-order cone programming (MISOCP) problem form using logarithmic transformations and linear relaxation methods. By iteratively solving and adding cut constraints, the fault section location and UAV dispatching decision can be determined, and RFI abnormalities can be identified. This strategy effectively harnesses the potential of UAVs for fault location in post-disaster scenarios within DS, offers valuable insights for post-disaster information collection and fault location, and enhances the situational awareness capabilities of DS following extreme events.