The Value of Data and Analytics in Storage Solutions

Stem’s sophisticated predictive analytics and machine learning applied to energy storage is providing major cost savings for businesses.
Published: Sat 10 May 2014

Energy storage start-up Stem’s proprietary data analytics and intelligent energy storage system is helping businesses to reduce their electricity costs without having to change their daily operations.

The Stem system offers an autonomous, real-time decision engine that alternates between battery power and grid power to optimize energy costs. Solutions combine predictive analysis techniques, cloud computing and big data with batteries to enhance energy efficiency at retail and industrial clients’ facilities.

The technology provides an automatic tool that decides in real time to load or offload energy from the client's energy storage system in order to optimise energy consumption levels. This solution also offers frequency regulation services that enable renewable energies to be integrated into electricity grids.

“More brains, less battery”

We asked Stem why predictive analysis is so critical to energy storage systems and Leesa Lee, Senior Marketing Director, explains it in a nutshell: “Battery storage is still prohibitively expensive for most commercial applications. Predictive analytics are critical in order to reduce the size of the battery (the most expensive component of the system). At Stem, we refer to this as “More brains, less battery”. Using predictive analytics, we are able to forecast energy usage peaks, and surgically charge and discharge to shave those peaks. This reduces demand charges (which are based on kW peaks) which are a significant component of U.S. electricity bills. Without these predictions, sites would require very large batteries in order to ensure the peaks are not missed.”

Investment potential

With regards to return on investment, Lee informed Engerati that customers are seeing payback periods in the 2 – 4 year range, which is very favourable compared to solar paybacks. In addition to these excellent economic results, demand is being driven by an increase in demand charges (while energy charges are decreasing) in many markets.

Investors such as Spanish power giant, Iberdrola and General Electric recognize the potential of this system and have recently invested US$15 million in Stem.

According to Diego Diaz, Head of Iberdrola´s Corporate Venture Capital program, Stem’s energy storage solution is improving the energy efficiency of its customers, as well as helping with renewable integration on the grid.

Colleen Calhoun, Senior Executive Director, GE Ventures-Energy, explains why her firm has invested in the start-up: “We look to invest in and partner with companies creating cutting edge technologies that can improve energy productivity and efficiency and Stem has been a leader in helping transform the economics of energy consumption without disrupting the way people use electricity.”

CEO of Stem, Salim Khan, says that the support of these “world class investors” has positioned Stem as the leading solutions provider for the rapidly growing energy storage market.

According to the latest report by Lux Research, the global grid storage market will grow nearly nine-fold to US$10.4 billion in 2017.

Energy storage market is growing

Stem’s Lee, told Engerati that in the US, there is an increasing focus on storage as can be evidenced by the number of procurement targets . A good example of this is the energy storage mandates recently announced in California where public utilities are expected to procure 1.3GW of storage by 2020. Lee says the market for storage is expected to grow significantly because there is increasing awareness of how beneficial storage can be to address some of the challenges facing utilities such as volatility and ramp rates due to the increasing penetration of solar.

With its new funds, Stem will have the opportunity to increase energy storage production to meet this untapped and rapidly growing market. This will give Stem the opportunity to expand its solutions to new customers, thereby increasing its sales.

Mr Khan points out that there is a new revolution about to take place at the edges of the power grid as new types of distributed energy options are introduced. Other startups like Noesis, Opower, Nest, Gridco and FirstFuel are using data analytics to make buildings run more efficiently. These are a new wave of smart grid companies that are turning to the cutting edge of IT, like machine learning, to make the power grid operate more like the Internet.