Editor's Note: This is the first in a four-part series examining the growing role of machine learning and artificial intelligence in the power sector. Tomorrow, we look at how regional grid operators are using AI to optimize operations. The future of the electric grid is undoubtedly cleaner and more efficient and distributed, with hefty doses of technology and machine learning helping to operate it all. But if you're expecting a system dramatically transformed, experts say you'll be left waiting. Artificial intelligence and machine learning are already helping utilities run their networks more efficiently, extending the life of equipment and helping to dispatch energy into markets more efficiently.

Just as power system operators are mastering data analytics to optimize hardware efficiencies, they are discovering how the complexities of artificial intelligence tools can do far more, and how to choose which to use. With deployment of advanced metering infrastructure (AMI) and smart sensor-equipped hardware, system operators are capturing unprecedented levels of data. Cloud computing and massive computational capabilities are allowing data analytics to make these investments pay off for customers. But it may take machine learning (ML) and artificial intelligence (AI) to address new power grid complexities. AI is a form of computer science that would make power system management fully autonomous in real time, researchers and private sector providers of power system services told Utility Dive.

If somebody hacked communications to grid-connected devices and interrupted a demand response (DR) event, peak demand might not be cut, capacity prices could spike and that somebody could make a lot of money. Because of the fast-rising number of grid-connected devices in DR programs like smart thermostats and water heaters and the even faster-rising number of smart phones and other Internet technologies through which customers communicate with DR programs, market manipulations like that are possible, cybersecurity experts from the Electric Power Research Institute (EPRI) told the Demand Response World Forum October 17. It is one of many potential intrusions of communications between utilities and customers with grid connected devices and distributed energy resources (DER), they said. To counter these threats, data analytics experts are using the laws of physics and unprecedented masses of data to find cybersecurity breaches. And their work is leading to machine learning (ML) and artificial intelligence (AI) algorithms which, though only just beginning to find actual deployment, are expected to soon advance the ability to identify patterns to the intrusions and raise the level of protection for critical power systems.