The U.S. Department of Energy will explore whether artificial intelligence could help electric grids handle power fluctuations, avoid failures, resist damage, and recover faster from major storms, cyberattacks, solar flares and other disruptions. A new project, called GRIP, for Grid Resilience and Intelligence Project, was awarded up to $6 million over three years on September 12 by the U.S. Department of Energy. GRIP is the first project to use artificial intelligence (AI) to help power grids deal with disturbances, says Sila Kiliccote, GRIP's principal investigator and director of the Grid Integration, Systems and Mobility lab at the SLAC National Accelerator Laboratory in Menlo Park, Calif. GRIP will develop algorithms to learn how power grids work by analyzing smart meter data, utility-scale SCADA (supervisory control and data acquisition) data, electric vehicle charging data, and even satellite and street-view imagery. "By looking at satellite and street-view imagery, we can see where vegetation is growing with respect to power lines, how long it takes to grow, and anticipate what the effects of high winds might have on that vegetation, such as pulling trees onto power lines during storms," Kiliccote says.

Research indicates that IoT and Machine Learning are more valuable to utilities when used in combination but there are hurdles to overcome first. Machine learning and IoT will enable utilities to better realize the next generation of the power grid: a distributed system with power flows among millions of things like distributed energy resources (DERs), microgrids and in-home devices. All of which will help utilities deliver clean reliable energy and greater customer choice. Utility respondents to new research from SAS and Zpryme, The Autonomous Grid, indicated that IoT and machine learning were more than market hype. These technologies are already delivering actionable results, say respondents.

Machine learning and the Internet of Things (IoT) have the power to create an increasingly autonomous grid that can eventually handle billions of endpoints on utility networks. But is the industry truly maximizing the benefits of either technology? Find out how utilities are using IoT and machine learning today, what they're planning for the future, recommendations on improving utilities' adoption of these technologies on a larger scale and more.