The urgent need for more grid automation

In 2016, Dr. Kyri Baker was a researcher at the National Renewable Energy Laboratory working on a new home energy management system. Called Foresee, the system reduced energy usage through machine learning algorithms that tracked consumption patterns and grid conditions. 

Today, Kyri is an associate professor at the University of Colorado Boulder, where she continues her research on machine learning applications for the power grid. Her work has expanded beyond home energy management to the transmission and distribution grids, and she is pioneering new techniques for power flow optimization. 

This week, Kyri talks with Brad about how utilities can use neural networks to reduce outage times with data they already have available. She also describes the machine learning algorithms she’s training to make power flow predictions more accurate. 

This podcast is produced by GridX in partnership with Latitude Studios. GridX is the Enterprise Rate Platform that modern utilities rely on to usher in our clean energy future.