Wildfire Risk-Informed Preventive-Corrective Decision Making under Renewable Uncertainty
This addresses wildfire threats to power grid stability for grid operators, but it is incremental as it builds on existing unit commitment and optimal power flow methods.
The paper tackled the problem of mitigating wildfire risks in renewable-rich power grids by developing a coordinated decision-making scheme using day-ahead and real-time information, resulting in increased system resilience across multiple risk levels while maintaining economic viability.
The increasing frequency and intensity of wildfires poses severe threats to the secure and stable operation of power grids, particularly one that is interspersed with renewable generation. Unlike conventional contingencies, wildfires affect multiple assets, leading to cascading outages and rapid degradation of system operability and stability. At the same time, the usual precursors of large wildfires, namely dry and windy conditions, are known with high confidence at least a day in advance. Thus, a coordinated decision-making scheme employing both day-ahead and real-time information has a significant potential to mitigate dynamic wildfire risks in renewable-rich power systems. Such a scheme is developed in this paper through a novel stochastic preventive-corrective cut-set and stability-constrained unit commitment and optimal power flow formulation that also accounts for the variability of renewable generation. The results obtained using a reduced 240-bus system of the US Western Interconnection demonstrate that the proposed approach increases the resilience of power systems across multiple levels of wildfire risks while maintaining economic viability.