You may have heard that new technologies in the clean energy sector are creating new jobs. But what does that really mean?
Researchers at the University of Washington have a $3 million grant to support emerging careers where energy science is combined with big data.
Inside the Pioneer Square neighborhood offices of Optimum Energy, Engineering Manager Fred Woo stands in front of 6 large, brightly colored screens. One has a map of the United States showing the locations of dozens of their clients. On others, spinning gears and bar graphs detail the power needs and usage of all these customers, most of which are using a lot of air conditioning.
“So from one look, we can see, you know, the status of every system. Is it optimized, is it not? how efficient it is,” says Woo.
Optimum Energy has been in business for about a decade. They say they’ve saved building operators such as hospitals and state universities millions of dollars, by improving the efficiency of heating and cooling systems.
“Our product is very powerful at that. It takes the biggest motors and biggest energy users in a building and reduces their energy use by half,” he says.
But for Optimum Energy, as for most companies in this sector, the power of the software has been somewhat limited by a shortage of engineering talent.That’s where the $3 million at UW comes in. The program is known by its acronym, DIRECT, which stands for Data Intensive Research Enabling Clean Technologies Associate Professor Jim Pfaendtner is the principal investigator who secured the grant from the National Science Foundation.
“The idea for this project came from graduate students coming to me and saying, hey Jim, this job looks awesome. It’s called Data Scientist, or Molecular Data Scientist. How do I get this job?" Pfaendtner said.
Pfaendtner and his team designed a curriculum that emphasizes getting students out on job sites for capstone projects.
Optimum Energy took part in the first round last year. Ryan Kastilani, a 24-year-old Ph.D. student in chemical engineering, says working there gave him the challenge of dealing with real data.
“Oftentimes when you take a class everything’s super neat, everything works out super nicely,” Kastilani says.
“But that’s not the real stuff. In the real stuff, there’s actual work to be done,” like discovering a faulty sensor that screws up your datasets, he explains.
The UW’s grant aims to create training curriculum that can be replicated nationwide. Other clean energy companies requiring these kinds of skills include those working on new materials for energy storage and conversion for things like batteries and solar panels.