Wildfire Risk Metric Impact on Public Safety Power Shut-off Cost Savings
Public Safety Power Shutoffs (PSPS) are a proactive strategy to mitigate wildfire risks by preemptively de-energizing power lines and redispatching generation. However, wildfire risk quantification is critical for the operational effectiveness of PSPS. Many existing PSPS formulations rely on the Wildland Fire Potential Index (WFPI) to relate wildfire risk to power system operations. However, this flammability-based wildfire risk correlates less strongly with observed wildfire ignition probabilities (OWIP) than the Large Fire Probability (WLFP). This wildfire modeling discrepancy can distort generation commitments, misinform line de-energizations, and increase real-time (RT) costs. Prior work avoided incorporating wildfire ignition probability (WIP) due to the complexity of modeling wildfire-driven failures as Bernoulli random variables, which introduces non-linear constraints. By leveraging the cross-entropy between WIP and true outages, we represent wildfire risk as the sum of each energized line's wildfire ignition log probability (log(WIP)), rather than relying on a WFPI proxy. A cross-entropy constraint models joint line failures in a tractable manner without enumerating all failure scenarios. A stochastic day-ahead (DA) unit commitment with the PSPS framework assesses the cost impact of mapping WFPI- or WLFP-based risk metrics to WIP on the IEEE RTS 24-bus and RTS-GMLC systems. Out-of-sample results show that mapping WLFP to log(WIP) in the PSPS optimization leads to more risk-aware decisions and reduces expected and worst-case out-of-sample costs. These findings underscore the benefits of incorporating probabilistic wildfire risk metrics to improve PSPS decision-making for wildfire-resilient power systems.