Ensuring the nation’s electrical power grid can function with limited disruptions in the event of a natural disaster, catastrophic weather or a manmade attack is a key national security challenge. Compounding the challenge of grid management is the increasing amount of renewable energy sources such as solar and wind that are continually added to the grid, and the fact that solar panels and other means of distributed power generation are hidden to grid operators.
To advance the modeling and computational techniques needed to develop more efficient grid-control strategies under emergency scenarios, a multi-institutional team has used a Lawrence Livermore National Laboratory (LLNL)-developed software capable of optimizing the grid’s response to potential disruption events under different weather scenarios, on Oak Ridge National Laboratory (ORNL)’s Frontier supercomputer. Frontier recently achieved a milestone of running at exascale speeds of more than one quintillion calculations per second.
As part of the Exascale Computing Project’s ExaSGD project, researchers at LLNL, ORNL, the National Renewable Energy Laboratory (NREL) and the Pacific Northwest National Laboratory ran HiOp, an open-source optimization solver, on 9,000 nodes of the Frontier machine. In the largest simulation of its kind to date, Frontier allowed researchers to determine safe and cost-optimal power grid setpoints over 100,000 possible grid failures (also called contingencies) and weather scenarios in just 20 minutes. The project emphasized security-constrained optimal power flow, a reflection of the real-world voltage and frequency restrictions the grid must operate within to remain safe and reliable.
