AutoGrid pulls in $9M to turn ‘big data’ into an energy source

AutoGrid, a Bay Area-based startup founded in 2011, pulled in $9 million to further the development of its software to help utilities and businesses control their energy usage.

[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":565576,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,enterprise,entrepreneur,","session":"D"}']

Its technology works by analyzing data collected by smart meters to allow operators to adjust to meet supply and demand. Its major customers include the City of Palo Alto Utilities and Sacramento Municipal Utility District, and it is reaching out to municipalities on the East Coast.

The data is collected from smart meters through sensors that are placed on the electric grid. By incorporating machine learning, which gets smarter over time, it can make predictions about energy consumption patterns inside buildings and across service regions. When enough data has been processed, it can forecast how much electricity might be needed in the coming hours or days.

“The capacity of the [smart] grid is not deployed efficiently,” said founder and chief executive, Dr. Amit Narayan (pictured, left). Smartgrids are the computer-based remote control and automation mechanisms that are used today to deliver electricity. In the past, workers had to manually gather data by reading meters and measuring voltage, and keeping an eye out for flawed equipment.

With the advent of analytics tools, we can begin to make predictions about the future and further optimize energy usage. “Up to 20 percent of the power-generating assets in some regions only get deployed ten or fewer days a year,” said Dr. Narayan.

Prior to founding AutoGrid, he taught on the topic of electronic design automation software at Berkeley and Stanford. He founded Berkeley Design Automation, which is used by more than 20 of the top 25 chip developers.

“AutoGrid is creating the brains for the smart grid. If you can analyze all of the data, you can predict what the electrical parameters of the grid will be under any situation and use that to remove inefficiencies from the electricity supply chain.” said Dan Ahn, managing director at Voyager Capital in a statement.

What’s interesting from a competitive standpoint is the company’s focus on pattern-recognition and predictive analysis. It faces competition from Enernoc, a real-time energy-management tool, and Silver Spring Networks, an energy networking supplier that is used by over 15 utilities across the U.S.

The company’s investors include Foundation Capital,  Voyager Capital and Stanford University. Last year, it won a $5 million grant from the U.S. Department of Energy program to devote to improving the product.

[aditude-amp id="medium1" targeting='{"env":"staging","page_type":"article","post_id":565576,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,enterprise,entrepreneur,","session":"D"}']

Image via Shutterstock