In power grids, operating points are set so that power generation can safely satisfy projected power demand. Between these setpoints (~10 minutes), however, variations in energy demand can trigger mechanisms that may de-energize infrastructure components and spread throughout the network. In severe cases, the result may be loss of power in significant portions of the grid.
In this webinar, Anitescu will discuss an approach for characterizing the distribution of these cascading failures due to uncertainty in demand and generation.
“Such cascading failures are rare and difficult to study empirically,” Anitescu said. He and his colleagues therefore have developed a kinetic Monte Carlo (kMC) model that efficiently simulates the distribution of these failures. To compute the kMC model, the researchers use large deviation theory together with simulation tools developed for studying chemical reactions.
“Calculating the AC optimal power flow (ACOPF) is a fundamental building block for the optimization of electrical power systems,” Anitescu said. “With this new approach, the cost of computing the probability of one failure is roughly the cost of one ACOPF.” Anitescu will discuss how this approach can be extended and used for power grid operations and planning.
The webinar is sponsored by the IEEE Power & Energy Society. It will take place October 7, 2020, at 11:00 AM EDT. The 45-minute presentation will be followed by 15 minutes of Q&A. For further information, go to this website.