Washington, Oct 5 : Future management of power networks may involve a little more brain power than it does today, if a team of Missouri University of Science and Technology researchers, led by an Indian-origin scientist, has their way.
The experts' new project involves literally tapping brain cells grown on networks of electrodes.
The Missouri S and T group, working with researchers at Georgia Institute of Technology, plans to use the brainpower to develop a new method for tracking and managing the constantly changing levels of power supply and demand.
Led by Dr. Ganesh Kumar Venayagamoorthy, associate professor of electrical and computer engineering, the researchers will use living neural networks composed of thousands of brain cells from laboratory rats to control simulated power grids in the lab.
From those studies, the researchers hope to create a "biologically inspired" computer program to manage and control complex power grids in Mexico, Brazil, Nigeria and elsewhere.
"We want to develop a totally new architecture than what exists today," says Venayagamoorthy, who also directs the Real-Time Power and Intelligent Systems Laboratory at Missouri S and T.
"Power systems control is very complex, and the brain is a very flexible, very adaptable network. The brain is really good at handling uncertainties," he added.
Venayagamoorthy hopes to develop a system that is "inspired by the brain but not a replica. Nobody really understands completely how the brain works."
The Missouri S and T team will work with researchers at Georgia Tech's Laboratory for Neuroengineering, where the living neural networks have been developed and are housed and studied.
A high-bandwidth Internet2 connection will connect those brain cells over 600 miles to Venayagamoorthy's Real-Time Power and Intelligent Systems Laboratory. Missouri S and T researchers will transmit signals from that lab in Rolla, Mo., to the brain cells in the Atlanta lab, and will train those brain cells to recognize voltage signals and other information from Missouri S and T's real-time simulator.
Venayagamoorthy's lab is capable of simulating a power grid the size of Nigeria's, or a portion of the combined New England and New York grid in the United States.
Traditional artificial neural networks (ANNs) have been around for years. Modeled after the brain, they are designed to recognize patterns and learn over time. But they don't work well with complex systems, Venayagamoorthy said.
He added: "As electric power and energy systems get larger and larger, the dynamics become more complicated, and the neural networks have to be scaled up.
"But as they scale up, they break down. It becomes more difficult for neural networks to learn and change in real time.
"They can learn online, but the learning is slow and sometimes the decision-making is very short-sighted."