With support from the National Science Foundation (NSF), a team at Rensselaer Polytechnic Institute (RPI) is developing software to enable real-time analysis of power grid data, a tool that will become more essential as the nation moves toward integrating more renewable power sources, the researchers say.
It often takes time for power system malfunctions to be found and fixed – at times, leading to larger system failures, says RPI. If operators could identify system disturbances as they happen and take action before they lead to large outages, the power grid would be substantially more reliable and resilient, the researchers explain.
Meng Wang, an associate professor of electrical, computer, and systems engineering at RPI, is developing software to make that real-time analysis possible.
“If something happens in the system, we want to know as soon as possible where it is and what type of event it is so that the operator can take actions to fix that,” Wang says.
Wang is working with Joe Chow, an institute professor of electrical, computer and systems engineering at Rensselaer, to develop machine learning and data analytics tools that can quickly extract information from the many measurements already being taken as operators monitor the power system.
Wang notes that the renewable energy from solar and wind can be very volatile, requiring the power grid to be more prompt and flexible in managing the power demand and supply.
“With the increasing integration of renewables, it is really essential for us to know what happens in the power system immediately,” Wang says. “We want to be able to balance the demand and the supply continuously.”
The Rensselaer team is also working with a team from Cornell University that is focused on developing security hardware tools aimed at fortifying the future power grid as it becomes both more intelligent and more digital.