Based in Downtown Los Angeles, Vertum was founded in 2009 with the mission of transitioning cutting edge atmospheric modeling research conceived at UCLA to the marketplace. Vertum’s team of UCLA professors and researchers developed software to model different effects within the atmosphere, which are primarily used for climate change projections, and ultimately the effects of climate change on various applications. Vertum has taken this modeling from the lab and applied it to revenue projections for wind power generation, among other renewables. We had a chance to visit their offices, and talk to Cameron Whiteman, Managing Partner & Co-founder, about the software tools they are developing from this research.
With the help of a recent SBIR Phase II grant from the DOE, Vertum Partners is developing software tools that process extremely large datasets to provide quantitative assessments of revenue variability at current and potential wind power sites, accounting for fluctuations arising from changes in weather. Cameron explains, “The data is gigantic, and extremely hard to model, even by wind farm developers. The wind farms, and turbines themselves, are gigantic and each utility scale turbine one at a given optimum time is going to produce enough electricity for as many as 1500 homes. You also have to remember that there is no feasible way to store electricity on such a large scale – there’s not anywhere near enough battery power to store electricity for even the city of LA for five minutes. As a result, all the electricity produced has to be used within that moment. In the wind power industry up until a few years ago, there was an across the board shortfall, where up to 10% less energy was produced than was forecasted when the farms were initially set up.” What this means is 10% less revenue than investors were expecting.
Those initial forecasts used daily averages which included large amounts of power generated in the middle of the night that cannot be sold at that time or stored. Essentially, for accurate forecasting, you need to breakdown the wind power generated during the times electricity is really in demand, and also take into account seasonal variation. In addition, wind power generated is not consistent. What happened yesterday is not necessarily what’s going to happen a year from now. Climate change is real and while uncertain, modeling programs like Vertum is developing can provide some predictability.
Vertum’s immediate focus is to be able to provide a tool that serves those that need a macro understanding of the returns of a wind power site, accounting for all of these fluctuations and dynamic information. Cameron told us, “The product we are developing really helps people understand how the wind site is going to perform. The purpose it serves is not wind farm site selection, which is determined primarily by land use, but rather, it can be used to provide information that helps lay out the wind farm to maximize its capability, and finance it. It is most sellable, and useful, to finance people and investors. The tool really clarifies what will come out of an investment in a wind farm, that is, the amount of power that the wind farm will generate, modeled off huge data inputs, helping financiers with risk assessment.” Essentially, Vertum’s software looks at all the uncertainties surrounding wind power generation, and performs probability analysis for different outcomes.
Cameron also went onto explain to us that the goal of the product is to provide information to encourage better decision making. And they are striving to do this at 1/10th the cost of anything currently available in the market. It will help banks and investors understand likely future outcomes for wind farm projects. With a better understanding of the risks and more confidence in the numbers, we will ultimately see an increased willingness to invest in such important projects.
The long term vision of the company is that there will be software tools that help the layperson model the future, as affected by climate history, and climate change. Cameron hopes that in the next decade, people will make housing or farming decisions based on answers provided by these software tools. For example, if you are choosing between buying a house in Malibu and Beverly Hills, you would be able to evaluate the likely impact climate change will have on each property, and factor that into your decision. However, this must be preceded by a significant amount of education and understanding both about the nature of the information provided, and its value. The most immediate downstream applications for the company, past wind power, also lie in other areas under renewable energy, such as offshore or solar modeling. Outside the renewables, there is the opportunity to help urban planners by improving the resolution of the modeling they do, such as the effect of temperature variability on tree planting, and other infrastructure building decisions.