“A new artificial neural network model created by Argonne scientists handles both static and dynamic features of a power system with a relatively high degree of accuracy.
America’s power grid system is not only large but dynamic, which makes it especially challenging to manage. Human operators know how to maintain systems when conditions are static. But when conditions change quickly, due to sudden faults for example, operators lack a clear way of anticipating how the system should best adapt to meet system security and safety requirements.
At the U.S. Department of Energy’s (DOE) Argonne National Laboratory a research team has developed a novel approach to help system operators understand how to better control power systems with the help of artificial intelligence. Their new approach could help operators control power systems in a more effective way, which could enhance the resilience of America’s power grid, according to a recent article in IEEE Transactions on Power Systems…”
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