Bringing Big Data to Smart Meters
Despite investing millions of dollars in smart meters, utilities have yet to fully capitalize on the data these two-way meters produce. Startup AutoGrid Systems is taking on the job of analyzing giant data sets so utilities can monetize that flow of data.
The Palo Alto, California-based startup today announced it has raised $9 million from venture capital firms and Stanford University, where founder and CEO Amit Narayan developed the company idea as director of smart grid research. The company had previously received grants from the Department of Energy’s ARPA-E agency and the California Energy Commission.
AutoGrid engineers have built software called the Energy Data Platform that collects and processes large quantities of data meters and sensors along the grid produce. “We’re trying to essentially create a brain for the grid,” says Narayan. Its first application, aimed at utilities, is for demand response, or automatically shedding power use at utility customers during peak times.
Utilities already run demand-response programs, either by using third-party providers or developing their own systems. Companies, such as EnerNoc and Comverge, run demand response programs for utilities, which has become an important tool is reducing demand during peak times, such as late afternoon during a heat wave when the air conditioning load stresses the grid’s capacity. In exchange for lowering power, utility consumers get some sort of rebate.
AutoGrid software service is a less expensive option than existing demand-response programs so more utilities can start these programs, Narayan says. The system analyzes grid usage patterns to predict power demand a day ahead, too, which means utilities and consumers can participate more often in load-shedding programs, he says.
The software collects data from smart meters or, using a standard called OpenADR, connects to hardware at commercial and industrial electricity users. Demand response is AutoGrid’s first application but it has plans for other specialized programs. For example, the software can be used to better integrate variable wind and solar power or manage electric vehicle battery storage to maintain grid balance.
With millions of smart meters and sensors inside buildings and the grid installed, data management and analytics is rapidly becoming a serious challenge for utilities. Narayan says it’s possible for a single utility to generate tens of petabytes of data a year. Given that sort of technical challenge, it makes sense that specialized companies such as AutoGrid Systems will emerge to make sense of all that data and help deliver on the potential of the smart grid.
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