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November 12, 2012
Texas Goes Live with IBM's Big Data for Smart Grid
By Tabitha Naylor, Contributing Writer
Somebody’s got to step in to collect, analyze and start delivering real-world value from big data that utilities that the smart grid delivers. Nowadays, for a lot of the activity in the smart grid, that’s the touchstone. From its new technology, hundreds of thousands of distribution grid devices and a confusing array of back-end software systems as well as utilities with tens of millions of smart meters strive hard to make the most of it.
In smart grid big data, IBM (News - Alert) is a giant and with partners around the world, to link up power meters, grid sensors, leak detectors for water networks, and other end devices into the back-end systems, it uses its IT heft to make them run. One of its earliest test-beds for its smart grid vision has been Texas, where IBM has been working with utilities like CenterPoint Energy (happily so far) and Austin Energy (News - Alert) (less happily).
IBM and big Dallas-area utility Oncor announced earlier this week that the latest achievement on this long-running relationship, is a big data platform that’s analyzing Oncor’s 118,000-plus miles of power lines, crunching data from its three million or so smart meters from Landis+Gyr and meter data management software from Ecologic Analytics (both owned by Toshiba (News - Alert)), and rolling out the results for both utility operations staff and customers via the state’s smart meter web portal.
“To be honest, it’s taken us some time to get here. What big data allows us to do, what we’ve announced today, is using that integration, both at the consumer level and at the optimization layer,” Michael Valochi, IBM’s Global Energy and Utilities Leader.
Oncor had to first build out the infrastructure and in order to start collecting data, the smart meters, grid sensors and communications networks had to be in place. Then it built the big data software and hardware infrastructure to start doing something with it.
Edited by Brooke Neuman
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