Analyzing the floods of data coming from smart meters, grid sensors and other grid-edge devices is an expensive and complicated undertaking for utilities.
Pushing that heavy IT lifting to the cloud, and managing the process as a service, is one way that grid vendors are trying to cut down on those costs and complications -- particularly when it comes to the most widely deployed grid device out there: the smart meter.
Cloud analytics platforms from General Electric, Landis+Gyr, Silver Spring Networks, Siemens’ eMeter, Oracle’s DataRaker are on prominent display at this week’s DistribuTECH conference in San Antonio, Texas. Smart meter vendor Itron just added its name to that list, with an analytics-as-a-service offering with utility Texas-New Mexico Power.
TNMP has installed about 125,000 smart meters, or about half its planned 240,000-meter deployment, that are linked by cellular networking provided by SmartSynch, which Itron bought in 2012 and has since renamed Itron Cellular Solutions. With its new analytics service, Itron will be measuring system performance and collecting data to deliver reports and present operational recommendations on applications including energy diversion detection, transformer load management, and outage and voltage data analysis.
These aren’t new data-crunching tasks for Itron -- it has launched analytics software for its electric, water and gas metering platforms over the past year. But this week’s announcement is the first time it’s offered these capabilities as a service that runs on servers in its data center. That’s part of a new common platform that it’s hoping to deliver to utilities, whether they’re using Itron’s OpenWay wireless mesh communications or cellular meters, across the gas, water and electric metering networks.
On the electric side, Itron’s analytics platform supports line-loss testing, energy diversion (i.e., energy theft) detection, outage analysis to help locate faults and speed power restoration, and some transformer load management modules that can be put into play for volt/VAR optimization (VVO). These constitute a short list of many of the key analytics operations we’re seeing from a range of contenders out there.
Of course, different analytics platforms get their data in different ways, and at different stages of the process that carries it from the endpoints where it’s created, so to speak, to the back-office big data systems that turn it into information about the grid. Just how these different approaches stack up in terms of their cost to deploy, versus the value that comes from what they deliver, is a matter for debate.
Add the host of “big data” challengers on the smart grid front, from startups like AutoGrid, C3 Energy, Trove, Opower and Verdeeco, to IT giants like IBM, SAS, Teradata, EMC and SAP, and you’ve got a long list of options to add to the mix. There’s no doubt that utilities are both ready to spend on data analytics and struggling to realize more value from the data that’s flowing in from the edges of the grid. GTM Research has pegged the value of the global utility data analytics market at a cumulative $20 billion between 2013 and 2020, growing from an annual spend of $1.1 billion this year to nearly $4 billion by decade’s end.