Grid reliabilityImproving Grid Reliability in the Face of Extreme Events
The nation’s power grid remains vulnerable to disruption from extreme events including wildfires, severe storms, and cyberattacks. Variable generation resources and load volatility also present operational challenges to grid stability. To mitigate disruptions before they snowball, grid planners and operators must be able to see these events coming and understand their potential impacts on grid reliability.
The nation’s power grid remains vulnerable to disruption from extreme events including wildfires, severe storms, and cyberattacks. Variable generation resources and load volatility also present operational challenges to grid stability. To mitigate disruptions before they snowball, grid planners and operators must be able to see these events coming and understand their potential impacts on grid reliability.
However, current tools aren’t up to the task of accurately modeling all the scenarios and interdependencies with the accuracy, scale, and speed necessary. A better approach that in turn requires more computing power is needed.
Enter ExaGO, a modeling and optimization platform for solving large-scale, nonlinear power grid optimization problems. Short for exascale grid optimization toolkit, ExaGO is open-source software that can take advantage of high-performance computing and emerging heterogeneous computing platforms to model and forecast the impact of extreme events and operational complexities on power grid reliability.
“The Exascale Computing Project at DOE was looking for specific applications that would be well-suited for this approach to computing,” said Shri Abhyankar, senior optimization scientist in the Electricity Infrastructure and Buildings Division at Pacific Northwest National Laboratory (PNNL). “Exascale grid modeling was an ideal candidate application, our sponsors agreed, and we got started with the ExaGO project.”
ExaGO is being developed by PNNL under the ExaSGD project, which involves five national laboratories and Stanford University and is funded by the U.S. Department of Energy Office of Science Exascale Computing Project. ExaSGD focuses on developing algorithms and techniques to address these new challenges and optimize the grid’s response to many potential disruptive events under different weather scenarios.
Software Now Available
After only 18 months of research and development, the PNNL team recently released the first stable version of ExaGO software. ExaGO can run on hardware ranging from laptops to exascale supercomputers, allowing high-fidelity grid models to be deployed on new and emerging accelerator-based computing architectures.
“ExaGO is a significant leap forward in power grid modeling,” said Slaven Peles, chief scientist for the Optimization and Control group at PNNL and principal investigator for the ExaSGD project. “The ability to quickly model highly complex scenarios at scale and assess their potential impact on power grid reliability is critical to implementing corrective measures in a timely manner.”
