Electric utilities are taking a course in machine learning to create smarter grids for tough challenges ahead. The winter 2021 megastorm in Texas left millions without power. Grid failures the past two summers sparked devastating wildfires amid California's record drought. "Extreme weather events of 2021 highlighted the risks climate change is introducing, and the importance of investing in more resilient electricity grids," said a May 2021 report from the International Energy Agency, a group with members from more than 30 countries. It called for a net-zero carbon grid by 2050, fueled by hundreds more gigawatts in renewable sources.

On any given day, the electric power industry's operations are complex and its responsibilities vast. As the industry continues to play a critical role in supporting global climate goal challenges, it must simultaneously support demand increases, surges in smart appliance adoption, and decentralized operating system expansions. Behind the scenes, there's the power grid operator, whose role is to monitor the electricity network 24 hours per day, 365 days per year. As a larger number of lower capacity systems (such as renewables) come online and advanced network components are integrated into the grid, generation becomes exponentially more complex, decentralized and variable, stretching control room operators to their limits. More locally, building owners and controllers (Figure 1) are being challenged to deploy grid-interactive intelligent elements that can flexibly participate in grid level operations to economically enhance grid resiliency (while also saving money for the building owner).

In 2010 I wrote that there were three sponsored research projects to solve the problem of safely inspecting and maintaining high voltage transmission lines using robotics. Existing 2010 methods ranged from humans crawling the lines, to helicopters flying close-by and scanning, to cars and jeeps with people and binoculars attempting to scan with the human eye. In 2014 I described the progress from 2010 including the Japanese start-up HiBot and their inspection robot Expliner which seemed promising. This project got derailed by the Fukushima disaster which took away the funding and attention from Tepco which was forced to refocus all its resources on the disaster. HiBot later sold their IP to Hitachi High-Tech which, thus far, hasn't reported any progress or offered any products.