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Mining Big Data for an Energy-Efficient Future

Mining Big Data for an Energy-Efficient Future
Natasha Balac, director of the San Diego Supercomputer Center's Predictive Analytics Center of Excellence, is at the forefront of an effort to develop a data infrastructure for a greener San Diego. (UC San Diego Publications / Erik Jepsen)

Processing and analyzing huge amounts of energy-usage data has helped make UC San Diego one of the greenest universities in the U.S., thanks in no small part to the San Diego Supercomputer Center (SDSC), an organized research unit of the university.

Now the center is moving beyond the university to take on a new challenge — creating a greener San Diego.

Sustainability has long been a focus at the university, where 92% of the energy is renewable, generated with solar panels and second-life batteries, with electric and hybrid vehicles used for on-campus transportation. When SDSC came onboard, energy-efficiency soared to an even higher level.

The center's contribution lies in its capacity to process what's known as "big data" — the staggering amount of information that pours into the world each day.

"It's not just large data. It's so fast it's like we have a fire hose of data coming at us," said Natasha Balac, director of SDSC's Predictive Analytics Center of Excellence.

But for Balac and her team, harnessing that onslaught of information is an exciting challenge — one that's crucial to increasing sustainability.

A main source of data about UC San Diego's energy usage is the university's "smart" microgrid, one of the most advanced in the world. What makes a grid smart is its ability to provide feedback on consumption from smart grid sensors on buildings, appliances and more.  By processing and interpreting the information, the system can drive reduced consumption, identify grid instability and more.

Take, for instance, this simplified example: It's a hot summer day at about 6 in the evening. People are coming home, cooking dinner, turning on dishwashers, washing machines, air conditioners — all of it putting a huge strain on the grid that might cause an outage.

Once you analyze the data and understand the pattern, you can achieve solutions in a variety of ways from conserving energy consumption at peak times to identifying buildings that need more solar panels. This has proven remarkably effective at UC San Diego.

"We have actually started saving about $850,000 per month in energy costs," Balac said.

Now the university has embarked on an even more ambitious undertaking — developing a data infrastructure for a greener San Diego. For this "cyberinfrastructure" project, they'll be analyzing more than just energy usage. They'll also be looking at gas, water, waste, transportation and traffic. The pilot program will include two condominium buildings, a restaurant, a sports stadium and the airport.

The San Diego initiative is also fulfilling one of the most important missions at SDSC's Predictive Analytics Center: closing the gap between government, industry and academia. They're joining forces with organizations like oSIsoft and Clean Tech San Diego, as well as the offices of the mayor and governor, all working with consumers to create a smarter, more sustainable community.

"The most exciting part is the impact it will make on a large number of people and on our future," said Balac. "That's pretty darn cool."

The White House thinks so too. In November, this San Diego initiative, along with another big data project at the analytics center led by the San Diego Supercomputer Center's Chaitan Baru, received special recognition from the Obama administration.


—Maxine Nunes, Brand Publishing Writer