One of the key trends we’ve seen in cleantech recently is what we call, colloquially, “the rise of the business case.”  When large companies and startups have been able to quantify the benefits of a given investment to customers – providing some sort of financial metric like an IRR, ROI or simple payback period – they have weathered the headwinds of a tough economy.  Examples include large energy services businesses like Johnson Controls, Honeywell, and Schneider Electric.  Startup examples include efficiency-related companies who can quantify their value propositions – names like Scientific Conservation and BuildingIQ in the building, and Lumenergi, Daintree, and Digital Lumens in lighting.

But in energy storage, making a business case can be very hard.  Not only is the data sometimes ambiguous/flawed/non-existent, building that data into a business case is difficult. Energy storage company Ice Energy, for instance, has a link to a 65 page guide for modeling the value proposition for distributed storage on their website.  Grid storage may be even more difficult; to make economic sense a deployment must (almost always) address multiple benefits.  But addressing certain benefits involves the opportunity cost of operating the device in a way that precludes others.  For instance, if you were to target ancillary services applications you have to discharge your storage device quickly, which might mean forgoing other applications like shifting load from times of low prices to higher prices.

Gathering data and performing the analysis necessary to make the storage business case, along with the associated challenge of using the storage device in a way to optimize its potential value, are the problems that Bay Area startup Powergetics is trying to solve.  The company is targeting energy storage for the commercial market not by developing a new battery, but by using data, software, and power electronics to operate batteries in a way that optimizes its value.

Imagine, for instance, that your company is charged more for energy use at certain periods in the day (this is usually not a hypothetical, especially in California).  To reduce your operating costs, you install a battery and store energy from the grid when prices are low.  You then use that energy when prices are high so you buy less of it from the (expensive) grid.  You do this every time there’s a price differential and there are up to two price differentials in a day.    Assuming you want the battery to last 10 years this requires: (2 cycles a day x 365 days a year) x 10 years=7,300 cycles.  But assume your lithium ion battery has only 4,500 cycles in it for this application.  So the problem becomes an optimization one: How do I use my limited cycles for the highest value?  Or, how do I maximize the marginal value of the kilowatt I choose to store?

And that is the problem that Powergetics is setting out to solve.  The company has raised several million dollars to date, and is raising a venture round right now.  While the company did not reveal many specifics about the product, we found it interesting for three reasons.  First, it aligns with the broader theme of the rise of the business case (see here for what we think of companies who don’t have one).  Second, it touches on the topic we will discuss in great depth at our flagship San Francisco forum in March – the role of data in cleantech.

Third and finally, it aligns to our view of the broader storage market.  Our research work indicates that it’s not enough just to store energy cheaply.  The energy stored has to be put to uses where the marginal value of that stored energy is high, and the available alternatives are either non-existent or more expensive.  Stay tuned for our forthcoming research briefing on storage where we flesh out this “marginal value of a megawatt” idea in  greater depth.