Heat Hunter
To track and improve Digital Realty’s PUE effectiveness, Apollo AI trained on a tremendous amount of historical operations data, and it continues to process additional data as it becomes available, Dessing explains.
Among other benefits of that education, Apollo AI can detect subtle temperature changes and other performance variances that suggest problems and then make recommendations to resolve them, he says. While some fixes are more involved than others, of the 18-gigawatt hours of identified energy savings by Apollo AI, about 14 gigawatt hours represent relatively quick remedies, he adds.
One of the speedier solutions involved Apollo AI’s discovery of heat around a chilled water filter hidden deep inside the bowels of a data center. That was an indication that the filter was clogged, which was putting an extra load on a pump to move the coolant, Dessing says. By replacing the inexpensive filter, energy usage dropped by 75 megawatt-hours per month in the summer, and at least 225 megawatt-hours per year, he reports.
Similarly, Apollo AI located a faulty three-way valve that was allowing heat to escape. Given that a single data center could have hundreds of filters and valves, the likelihood of a human finding tiny heat fluctuations in such a labyrinth would be slim.
“These were very nice findings that the human brain just wouldn’t detect,” Dessing says. “There are a lot of operational specialists who can do magic with tools like Excel, but the amount of data that our AI is working with goes far beyond that level.”
Still, Apollo AI hasn’t replaced the expertise of those engineers, who plan and implement remediation projects based on the technology’s recommendations. For that reason, in the earliest days of Digital Realty’s AI development communication has been key to the program’s effectiveness, Dessing says.
“We didn’t want to present this as a system that was taking over their jobs, but something that was going to make their life easier,” he says. “We’re really enabling the data center engineers to have more insight; they can analyze everything recommended by the AI and focus their efforts on projects that have the biggest impact.”
