Outage Management of Active Distribution Systems With Data Fusion From Multiple Sensors Given Sensor Failures

Complex scenarios of multiple faults, sensor failures, and the fault current from distributed generations (DGs) pose a challenge for efficient outage management in distribution systems. To solve the issue, this study proposes a new algorithm for sequential determination of outage scenarios with data fusion from multiple sensors, i.e., smart meters and remote fault indicators (RFIs). To this end, an active distribution system is modeled as an undirected graph with vertices representing load zones, protective devices and RFIs, and edges denoting their adjacency. Set operation is proposed to derive the expected RFI alarms for each load zone if faulted and smart meter outage reports for each protection device. This serves as an input to the proposed evidence-driven methodology to sequentially quantify the credibility of the potential outage scenarios supported by RFIs and smart meters. By ranking the credibility, the most credible scenario of the activated protection and fault location, either on the primary feeder or laterals, is determined for expedited power recovery. Test cases of the IEEE System and a utility circuit show that the proposed approach outperforms the state-of-the-art technologies in terms of its accuracy and computational efficiency, leading to more efficient outage management of distribution systems.