Power companies, for example, can now examine power-usage trends in 15-minute increments, whereas historically they were only able to examine usage over a period of days.
Southern California Edison, for instance, realized through its big data trial that some power-usage patterns it thought indicated fraud were perfectly legitimate upon closer examination. Edison now doesn't get as many false positives, Podorsky said.
"There was some lack of appreciation of what to do with the data," said John Simmins, EPRI technical executive. "It has taken them time to crystallize [their plans]. They are starting to do that now."
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Measuring the waves of the alternating current that pulse through the grid to see if there are slight variations in demand helps utilities decide which power plants to turn on and, in particular, how to efficiently use high-priced peaking units—generators used only when demand is unusually strong because of either extremely warm or cold weather. Big data applications will also make new types of generating technologies, including solar and wind, work better within the integrated grid, Simmins said.
Utilities can also better identify critical equipment in need of replacement, such as transformers, which can cause power outages when they fail.
"It saves us money and customers headaches," said Darren Shepard, director of meter systems and repair operations for American Electric Power. "We are starting to change transformers on a scheduled basis versus having them fail whenever. It's definitely a plus."