SMARTER STRATEGIES

Free iPhone App Forecasts ROI for Wind Generation

John Jainschigg | Date: 09-28-10 | Comments

A new iPhone app for weather does a lot more than predict rain. Vestas Weather, designed by the Danish wind energy firm Vestas, is being used to estimate the likely performance of wind generators.

Vestas Weather, a new iPhone app produced by Danish wind energy firm Vestas, is a nifty and practical tool for weather watchers that also offers a fascinating glimpse into the economics of wind generation. Bonus: Working with Vestas Weather gives insight into technologies now being used to sense and predict the behavior of complex systems.

The application is fairly simple. The iPhone detects your location and, via the Net, bangs it off a global database and predictive weather simulation maintained by Vestas' internal Siting and Forecasting division to help manage placement of wind turbines and predict the power they'll generate�a system served with real-time data from more than 40,000 of Vestas' own turbines, installed around the world, as well as other sources of meteorological info.

You get a range of views on current local weather, as well as hourly predictions several days into the future. Weather data is resolved to about 3-km resolution�about four times better than standard weather maps. Vestas Weather also features alarms that can warn you (for example) when prevailing conditions are likely to change.

Using this data, Vestas Weather can instantly predict the likely performance of a Vestas V112 3MW wind generator (the company's latest turbine, aimed primarily at utility companies) at your location, offering values for kwh output and average CO2 offset obtained.

The nifty iPhone app predicts the likely performance of wind generators.

Clearly, this is little more than a brand-specific sales gimmick in its present form. The iPhone is just being used to input GPS coordinates; the app could as easily enable entry of arbitrary coordinates by Zip code or via a maps interface.

It would also be interesting to be able to enter characteristics of arbitrary wind turbines, small and large, and use Vestas' database and engine to predict their performance. Enabling these features, however, implies a non-trivial exercise in user-interface design (to allow direct entry of turbine specifications), or would require someone to create and maintain a comprehensive database of all the world's turbines (though it's hard to believe someone hasn't done this already�perhaps Vestas itself).

Finally, it seems like it would be critical to real-world feasibility analysis to factor in the method conventionally used to generate power near the site (e.g., "dirty" coal versus "clean" hydro), to measure real (as opposed to notional) benefit.

Still, though it falls far short of being an actual site-analysis tool (or even a comprehensive sales tool for Vestas reps), Vestas Weather makes some important points about the economics and psychology inflecting the transition to greener power sources, and about the educational mission of proponents and solution vendors. Of these, the most important is the implicit assertion that advanced meteorological simulation, bolstered with ever-richer real-time data, is an accurate tool for predicting wind generator performance on the ground. Predictability�crucial to ROI analysis, assumption of debt and risk�is looking more and more like an inherent benefit of green energy.

And power-sellers are paying attention to that, especially now that it's getting harder to predict or contain the rising cost of fossil fuels and estimate the impact of expected regulations on the bottom line.