  Public safety power shutoffs (PSPS) are a common pre-emptive measure to
reduce wildfire risk due to power system equipment. System operators use PSPS
to de-energize electric grid elements that are either prone to failure or
located in regions at a high risk of experiencing a wildfire. Successful power
system operation during PSPS involves coordination across different time
scales. Adjustments to generator commitments and transmission line
de-energizations occur at day-ahead intervals while adjustments to load
servicing occur at hourly intervals. Generator commitments and operational
decisions have to be made under uncertainty in electric grid demand and
wildfire potential forecasts. This paper presents deterministic and two-stage
mean-CVaR stochastic frameworks to show how the likelihood of large wildfires
near transmission lines affects generator commitment and transmission line
de-energization strategies. The optimal costs of commitment, operation, and
lost load on the IEEE 14-bus test system are compared to the costs generated
from prior optimal power shut-off (OPS) formulations. The proposed mean-CVaR
stochastic program generates less total expected costs evaluated with respect
to higher demand scenarios than costs generated by risk-neutral and
deterministic methods.
