New Software Tool Could Push Wind Energy Into Mainstream

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The US Department of Energy’s National Renewable Energy Laboratory believes that a new software tool it has been developing could push wind energy into the mainstream and past the Department of Energy’s goal for 20% of all energy coming from wind energy by 2030.

The software tool, called Simulator for Wind Farm Applications (SOWFA), is being developed at the National Renewable Energy Laboratory (NREL) to calculate how a number of variables affect the air flow and energy production at wind farms. According to the NREL, SOWFA’s “key innovation” is its ability to simulate an extensive range of scale — from regional weather patterns down to the space between wind turbines and down even further to the movement of electrons. SOWFA’s ability to calculate the impact of undulating ground, turning blades, surface temperatures, and other variables that affect air flow and energy production could be the last little push needed to increase efficiency at wind farms to bring them up to cost parity with fossil fuels.

In the Energy Systems Integration Facility (ESIF) Insight Center, NREL Senior Engineer Pat Moriarty, left, and NREL Senior Engineer Paul Fleming review velocity (blue) and turbulence (yellow) in a simulation of the Lillgrund Wind Farm in Denmark. The researchers have written the open-source software tool Simulator for Wind Farm Applications (SOWFA), which can calculate how undulating ground, whipping blades, surface temperatures, and other variables alter the air flow and energy production at wind farms. Image Credit: Dennis Schroeder, NREL

This open source software is the first to enable developers to improve the performance of a whole wind farm, and not just the individual turbine.

One example of how SOWFA can help wind farm developers is in managing the impact one wind turbine has on its fellows downstream. If a wind farm is laid out in rows and rows of wind turbines, an issue that can arise is the disturbance the foremost wind turbine has on those turbines further down the line, sometimes causing a calm spot such as behind a tree or building to flow downstream. The ramifications on the overall output of a wind farm in these situations can be dramatic, with each wind turbine disturbing the energy generating ability of the turbine behind it.

SOWFA, however, can show turbine manufacturers, wind farm developers, or investors how a yaw can impart a thrust that curves that wake around the downwind turbine.

“Wake, from a power perspective, is lower-energy wind,” said NREL Senior Engineer Paul Fleming, one of the engineers using SOWFA in his research. “If you can move away that deficit of energy, you will have faster winds and more overall production at the wind farm.”

“In the past, wind farms have relied on dissipation to control that energy loss—they just move the turbines farther away from each other,” added NREL Senior Engineer Pat Moriarty, a leader of the SOWFA team. “Now, we can control it in a different way. And there are other ways to achieve more control.”

The NREL has a complete write-up on the SOWFA development and its various applications that is well worth a read.

In the long-term, however, software development such as SOWFA will have incredible impact on the proliferation and impact wind energy has on the overall energy scene. As the NREL said, wind energy only needs a very little nudge to become cost-competitive with fossil fuel energy sources — and that is going to be something investors and governments alike tune into.

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Joshua S Hill

I'm a Christian, a nerd, a geek, and I believe that we're pretty quickly directing planet-Earth into hell in a handbasket! I also write for Fantasy Book Review (, and can be found writing articles for a variety of other sites. Check me out at for more.

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13 thoughts on “New Software Tool Could Push Wind Energy Into Mainstream

  • While this might be revolutionary in terms of computational fluid dynamics applications, I can’t see it as anything other than another small incremental improvement in WT farm cost/efficiency.

    • Right, and “wind energy only needs a very little nudge to become cost-competitive with fossil fuel energy sources”

    • I agree. Also:

      “This open source software is the first to enable developers to improve the performance of a whole wind farm, and not just the individual turbine.”

      It might be the first open-source software to do that, but commercial software to do it has been available for years (decades even). It might come as a surprise to some, but companies building multi-million dollar wind farms don’t just spunk the turbines down at random.

  • Joshua, what’s the number you’re using for cost parity with fossil fuels?

    Non-subsidized wind in the US is now 4 cents. What fossil fuel generation can be brought on line for less?

    • Existing Australian brown coal plants have a marginal operating cost of under two Australian cents a kilowatt-hour on account of how their coal is basically free. Killing people as a result of burning the coal is also free. And killing their own workers is mostly free too. Life expectancy for a brown coal plant worker is about 15 years below average. And the marginal operating cost of black coal is about three cents a kilowatt hour. But no new fossil fuel capacity can beat new wind at four US cents a kilowatt-hour. Not in Australia and not anywhere else that I’m aware of. It’s just unfortunate that we have a lot of existing coal capacity and people who are willing to behave evilly and kill (indirectly) to make a buck.

  • Joshua: “… could push wind energy into the mainstream …”
    Oh dear. You know better. 318 GW (end 2013) (link) isn’t mainstream?

  • It will be easier to integrate lots of wind onto the grid once wind farms automatically regulate their power output. This might be achieved through a combination of super capacitors for second-to-second regulation and prop feathering for longer time scales (i.e. each turbine usually grabs 80-90% of the wind, but could bite more or less by angling its blades). With the increasingly accurate local weather forecasts now becoming available, a farm could bid smooth power onto the grid hours ahead of time.
    If a reduction in wind power can be forecast an hour ahead, that’s lots of time to spin up an idle gas plant.

    • Fifteen minutes is plenty for new design gas turbines

      • Ontario IESO has many days ahead wind forecasting. I use it myself to determine the best time to charge my EV. The IESO has built tools to do prediction of solar as well, but has not made that public (yet).

        Wind is 250MW right now, and will go to 2500MW one day from now, so I am going to use up most of my battery tomorrow on my commute and charge tomorrow evening and the day after.

        • Excellent. And the grid should give you a preferred rate for taking energy when they have a surplus and avoiding consumption when supply is taxed.

          Smart charging of EVs is the route to a renewable grid with the least amount of storage.

          • Ontario has smart meter implemented, and we are billed for high, medium and low demand periods.

            Unfortunately, the political party in charge have caved in and unfortunately the low demand starts at 7pm until 7am, but the reality is it should actually be 11pm-7am, but that would be harder for some voters to accept.

            I only charge during low demand period, which corresponds to overnight.

            I’d far rather the smart meters be used to properly charge people during peaks and lower cost during trough, rather than the time periods currently used.

            Anyway, large power users in the Province of Ontario can be charged based on their usage during the monthly peak periods. We also have demand response programs to reduce industrial load during peaks.

            Really, Ontario has pretty advanced management of the power grid, I just wish the politics would get out of the way…

    • Wouldn’t have to go to the expense of SCs, simple batteries (as standard in GE turbine towers) are enough for smooth over sub-sec to mins time frame. If farm want to shift over hours (to sell at higher price) then it is a much bigger storage. The difference of storing so 10-20% of output for 5-10 mins; orders of scale different from 100% for 4 hours. That is 50-200 units verse 24k units. If you are selling in 15min block, it is based on a several factors:
      – how much wind varies over that 15 min
      – how far in advance you need to be able to say how much
      – Cost to store kWh

  • One of the ways this will help in the future is the ability to add more turbines to existing wind farms such that the set backs from residential properties are not affected, but the turbine density can be increased on existing sites where the permitting and environmental reviews have already been completed in years past, and thus the ability to scale up is a matter of adding some more windmills to an existing facility.

    Here in Ontario, with 2.5GW of nameplate wind capacity now, and rising to 7GW before 2020, our need to add density as listed in the article will not be a pressing concern

    Ontario province wide usage of 22GW in the shoulder season (spring/fall) when wind power production peaks around 7GW, would be 30% wind. Adding to that is impractical until the base load Nuclear plants finally age out as they will do over the next decade…

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