The most extensive blackout in North American history occurred on Aug. 14, 2003, affecting an estimated 55 million people in nine U.S. states across the Midwest and Northeast and the Canadian province of Ontario.
Such high-impact outages are rare, and Kibaek Kim, a computational mathematician at Argonne National Laboratory, aims to keep them that way. He's in the second year of a five-year, $2.5 million Department of Energy Office of Science Early Career Research Award to develop data-driven optimization algorithms that account for power grid uncertainties.
"Right now, one of the issues in the grid system is that we have a lot of distributed energy resources," says Kim, who received his doctorate from Northwestern University before joining Argonne's Mathematics and Computer Science Division. Such resources include solar panels, electric storage systems, or other energy-related devices located at privately owned homes or commercial buildings. "These resources are not controllable by system operators – utilities, for example. These are considered as uncertain generating units."
Such components put uncontrollable and potentially risky uncertainties into the grid. If the system somehow becomes imbalanced, "it can lead to power outages and even wider-area blackouts," Kim notes. "The question we're trying to address is how to avoid these blackouts or outages, how to make the system reliable or resilient."
From ASCR Discovery
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