The Smart Electric Power Alliance (SEPA) recognizes the need for peer exchange and expert guidance on AI. At February’s RE+ Northeast conference in Boston, SEPA’s Emerging Technology team hosted a panel discussion on the current role and value of one form of AI – machine learning – for grid modernization in the Northeastern US. Thank you to Alexina Jackson with the AES Corporation, Sreedhar Sistu with Schneider Electric, David Stuebe with Camus Energy, and Mark Waclawiak with Avangrid for making the trip to Boston to join this panel. About half of our audience members said they already use AI in their work, but all leaned in close to learn from these experts. It was exciting to hear how utility operators, technology firms, and others are innovating to use AI here and now– as well as what to expect from this fledgling technology as its full capabilities unfold.

We learned that AI and machine learning are a good fit for many of the changes we need to make to optimize the electricity grid. This includes making more refined predictions about EV adoption, providing sharper and earlier visibility into where tree trimming and asset maintenance are needed the most, calculating new dynamic line ratings to maximize existing transmission corridors, and more. Panelists shared a consensus agreement that all AI/ML applications still require humans to think critically about data inputs and model design, and remain in the loop to oversee their use, take action based on the results, and monitor and calibrate performance. With several years of results coming in, panelists also explained how they’re measuring outcomes of AI investment today and why it is poised to help utilities develop innovative approaches for delivering safe, reliable, affordable, and low-carbon electricity to their customers. This blog captures what we learned from the four experts at RE+ Northeast.