Highlights of project output

Submitted manuscript

I. Romero, N. Chiang, I. Aravena, R. Marcia, N. Petra, JP. Watson, C. G. Petra, Wildfire-driven N-k contingency generation for security-constrained AC optimal power flow in the California power grid, submitted, 2026. PDF.

Submitted manuscript

C. G. Petra, A Proximal Oracle Sequential NLP Algorithm for Constrained Nonsmooth Optimization, 2026. PDF.

Accepted paper

T. Su, J. Zhao, E. M. Constantinescu, C. G. Petra, Multi-Fidelity Dynamic Line Rating Fusion for System Load Margin Enhancement with Large-Scale Offshore Wind Generations , IEEE Transactions on Power Systems, online, 2026. DOI .

Power grid short-term response to wildfires

We developed capabilities that intersect wildfire paths (both realtime probabilistic forecasts and historical data) with power grids. This allows detecting grid components that may be affected by wildfire and building a list of N-k contingencies. Nonlinear N-k security-constrained ACOPF models are used to optimally and safely position the grid with respect to this contingencies. Test cases using California test system and California wildfires are available here.

ExaJuGO: a Julia library for SC-ACOPF

tsSLOPE

tsSLOPE integrates learning models for transient stability into ACOPF models for simultaneous optimization via interior-point algorithms and automatic differentiation.