Tying quantum computing to AI prompts a smarter power grid

Fumbling to find flashlights during blackouts may soon be a distant memory, as quantum computing and artificial intelligence could learn to decipher an electric grid's problematic quirks and solve system hiccups so fast, humans may not notice. Rather than energy grid faults turning into giant problems--such as voltage variations or widespread blackouts--blazing fast computation blended with artificial intelligence could rapidly diagnose trouble and find solutions in tiny splits of seconds, according to Cornell research forthcoming in Applied Energy (Dec. 1, 2021). "Energy power system failures are an old problem and we are still using classic computational methods to resolve them," said Fengqi You, the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering in the College of Engineering. "Today's power systems can benefit from AI and the computational power of quantum computing, so power systems can be stable and reliable." You, along with doctoral student Akshay Ajagekar, are co-authors of "Quantum Computing-based Hybrid Deep Learning for Fault Diagnosis in Electrical Power Systems."