A method for variance-based sensitivity analysis of cascading failures

Cascading failures of relay operations in power systems are inherently linked with the propagation of wide-area power system blackouts. In this paper, we consider a power system cascading failure as an indicator matrix encoding: what power system relays operated within a cascading failure inherently capturing the component and the sequence of tripping events. We propose that this matrix may then be used with extended forms of variance-based sensitivity estimators to quantitatively rank how sensitive observed power system cascading failures are to power system variables, considering overall system cascading failures as well as cascading failures grouped by network area and relay types. We demonstrate our proposed method by investigating the sensitivity of cascading failures to relay parameters, system conditions, and fault location using a version of the IEEE 39 bus model modified to include protection relays, wind farms, and tap-changing transformers. Input power system variables included: system operational scenario, disturbance location, relay parameters or thresholds. The Case Studies' results confirm the method's utility by successfully generating relative rankings of input variables' importance with respect to cascading failure propagation. The results also show cascading failures' sensitivity to input variables to be high due to non-linear relationships between input variables and cascading failures.