POWER-GRID RESILIENCEReached: Milestone in Power Grid Optimization on World’s First Exascale Supercomputer
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.
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.
“Because the list of potential power grid failures is large, this problem is very computationally demanding,” said computational mathematician and principal investigator for LLNL Cosmin Petra. “The goal of this project was to show that the exascale computers are capable of exhaustively solving this problem in a manner that is consistent with current practices that power grid operators have.”
Today, grid operators are only capable of solving approximations of potential failures, and the decisions on how to handle emergency situations usually require a human, who may or may not be able to determine how to optimally keep the grid up and running under different renewable energy forecasts, according to Petra. For comparison, system operators using commodity computing hardware typically consider only about 50 to 100 hand-picked contingencies and 5-10 weather scenarios.