Wildfire Risk Metric Impact on Public Safety Power Shut-off Cost Savings

TL;DR

This paper compares wildfire risk metrics, WFPI and WLFP, in a power shutoff cost model, showing that using WLFP reduces expected real-time costs by nearly 15% in a test system.

Contribution

It introduces a deterministic approach to incorporate wildfire ignition probabilities into power shutoff optimization, improving cost savings over traditional risk metrics.

Findings

Using WLFP-based risk metrics reduces expected real-time costs.

Mapping WLFP to log(WIP) improves cost efficiency in power shutoff planning.

The approach achieves nearly 15% cost reduction in the test system.

Abstract

Public Safety Power Shutoffs (PSPS) are a proactive strategy to mitigate fire hazards from power system infrastructure failures. System operators employ PSPS to deactivate portions of the electric grid with heightened wildfire risks to prevent wildfire ignition and redispatch generators to minimize load shedding. A measure of vegetation flammability, called the Wildland Fire Potential Index (WFPI), has been widely used to evaluate the risk of nearby wildfires to power system operation. However, the WFPI does not correlate as strongly to historically observed wildfire ignition probabilities (OWIP) as WFPI-based the Large Fire Probability (WLFP).Prior work chose not to incorporate wildfire-driven failure probabilities, such as the WLFP, because constraints with Bernoulli random variables to represent wildfire ignitions could require non-linear or non-convex constraints. This paper uses a deterministic equivalent of an otherwise complicating line de-energization constraint by quantifying the wildfire risk of operating transmission line as a sum of each energized line's wildfire ignition log probability (log(WIP)) rather than as a sum of each energized line's WFPI. A day-ahead unit commitment and line de-energization PSPS framework is used to assess the cost differences driven by the choice between the WFPI and WLFP risk metrics. Training the optimization on scenarios developed by mapping WLFP to log(WIP) rather than mapping the WFPI to log(WIP) leads to reductions in the total real-time costs. For the IEEE RTS 24-bus test system, mapping transmission line WLFP values to log(WIP) resulted in a 14.8 % (on average) decrease in expected real-time costs.