## Quickest Line Detection and Identification Schemes

**Xichen Jiang with adviser A. Domínguez-García**

Fast and reliable line outage detection for power system transmission line outages is crucial for maintaining reliability in the power grid. Current methods to detect these line outages rely on a system model obtained offline. This can be inaccurate due to bad historical or telemetry data. We propose a model-free statistical algorithm for detecting line outages and show that it has better performance than other schemes. Our algorithm is based on the cumulative sum (CuSum) test from the quickest-change detection literature. It exploits the statistical properties of the measured voltage phase angles before, during, and after a line outage, whereas other methods only utilize the change in statistics that occurs at the instant of outage. We also devise a method to optimally set the thresholds for the CuSum algorithm so that for a fixed false alarm rate, detection delay is minimized. Simulations are performed on the IEEE 14-bus system, shown as a one-line diagram in Figure 28. Figure 29 presents a comparison of various statistical detection schemes for line outages. For a given false-alarm rate, our proposed algorithm performs better than others. This research is funded by NSF.