Team led by Daniel Bienstock Wins $530,000 in DOE’s Grid Optimization Competition

Group places high in competition, which is focused on developing software management solutions for power grid problems.

Dec 07 2021 | By Holly Evarts

Daniel Bienstock, Liu Family Professor of Industrial Engineering and Operations Research and professor of applied physics and applied mathematics, and his team, including colleagues from Northwestern University and Artelys, a French software company, won the second-place prize of $530,000 in the U.S. Department of Energy’s Advanced Research Projects Agency-Energy’s (ARPA-E) Grid Optimization (GO) Competition.

ARPA-E funds early-stage projects related to energy and the grid, with an eye toward potential startups. This GO competition focused on the Alternating Current Optimal Power Flow problem, a complex computational task used to decide how to operate a power grid network so as to safely and robustly meet electricity demand at minimum cost in large geographical areas, such as New York State, New England, California, or Texas. Teams had to develop software to handle a large number of test cases involving very large networks.

This task gives rise to a complex computation that combines engineering, physics, mathematics, and computer science. There were 21 competitors and two rounds. The computation was so complex that scoring the competitors took about two months. Said Bienstock, “The idea is to break down barriers to empower widespread, fast adoption of emerging grid technologies to save billions of dollars in the energy sector. We were really happy to win the first round and come in second in the second.”