A Startup’s Smart Batteries Reduce Buildings’ Electric Bills
Stem uses data analytics and large batteries to cut electricity costs in commercial buildings.
Systems that combine on-site batteries with software that responds to electricity prices and predicts a building’s energy use promise to save money while also making renewable energy sources more practical.
An energy startup called Stem has developed a battery for commercial buildings that’s clever enough to predict—based on the price of electricity—when to store power and when to release it. The market for the company’s technology is limited for now, but its product hints at how distributed energy storage and management could transform the grid.
A building’s owner can save money by analyzing energy-use trends and changing the thermostat settings in response. Dozens of companies are developing analytics software aimed at such efficiency improvements.
Stem, based in Millbrae, California, combines this “big data for buildings” technique with on-site energy storage. The batteries aren’t just intended as backup power. Instead, in concert with software, they’re part of a system designed to allow a building to use the cheapest form of power available at any given moment, whether that power comes from Stem’s batteries or from the grid.
The system uses algorithms adapted from the financial industry to predict a building’s power use on an hour-by-hour basis. The battery can start serving power the minute a higher price comes into effect—at times of peak use—or avoid the fees sometimes triggered by utilities when a building consumes too much power at a given time.
“This sort of thing was not possible five or six years ago. For every given site, we will literally run millions of simulations a day,” says Stem founder and executive vice president Brian Thompson, a former IT professional who developed high-volume e-commerce systems.
Stem’s batteries are stripped-down lithium-ion automotive batteries linked to power electronics designed to quickly switch between partially powering a building or charging from the grid. The bulk of the analytics are done over the Internet and sent to an on-site computer, which uses machine-learning techniques to improve its energy forecasts. The system can be bigger or smaller based on the number of batteries used, but can be as small as a small refrigerator or dishwasher.
A number of companies already use on-site power generation to capitalize on the difference between peak and off-peak rates. Stem, which was hatched at the Wharton Business School, had initially planned to combine rooftop solar power with batteries.
In California, commercial customers have a complex set of rates designed to lower peak-time demand. Sophisticated pricing structures make a price-optimizing system more worthwhile. With Stem’s system, Thompson says, customers don’t need to change their behavior and can still lower their bills between 5 and 15 percent.
Batteries located at buildings could also add storage to the grid. This would make electricity more reliable and allow for higher penetration of technologies like wind and solar, which produce power intermittently. Utilities have started to use batteries to buffer the grid, but they’re not in wide use because of the cost.
A network of smaller computerized batteries designed to lower a building’s energy bills could help, Thompson argues. He notes that a hotel with about 100 rooms can use a battery with a capacity between 50 and 100 kilowatt-hours, or two to four times bigger than the battery in the Nissan Leaf.
“As battery prices and the prices of computing and data and bandwidth drop, we’re going to see these types of devices in every building in the world, whether it’s in 20 or 30 years,” Thompson says. “These types of systems will allow us to move to a 100 percent renewable future.”
In the near term, the company has set its sights on California and states on the East Coast with similar electricity pricing schemes. Stem is pilot testing with small and medium-sized businesses in about 20 industries, and has deliberately chosen not to sell through slow-moving utilities.
But scaling up with direct sales could become a problem, says Jaideep Raje, an analyst at Lux Research. Energy startups usually need to partner with large corporations or utilities to get legitimacy and gain access to customers. “The smart money would say that as go the large utilities or large industrial players like Honeywell or Johnson Controls, so will go the industry,” he says.
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