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Google's DeepMind Can Predict Wind Patterns a Day In Advance (engadget.com)

Posted by BeauHD on from the predicting-the-future dept.

technology_dude writes: Google's DeepMind can predict wind patterns one day in advance. "Beginning last year, [Google and DeepMind] fed weather forecasts and existing turbine data into DeepMind's machine learning platform, which churned out wind power predictions 36 hours ahead of actual power generation," Engadget reports. "Google could then make supply commitments to power grids a full day before delivery." According to the report, this makes the energy generated by its wind turbines more valuable (by roughly 20%). Is this a blow to Big Blue who purchased The Weather Channel's Weather.com to showcase Watson, or is it news just because it's Google?

32 of 57 comments (clear)

  1. But can it predict.. by h33t+l4x0r · · Score: 5, Funny

    A butterfly flapping it's wings in Brazil?

  2. So what? I can do that. by alvinrod · · Score: 3, Funny

    So what? I can do that.

    My predictions rarely turn out to be correct, but that's besides the point.

  3. So can any other prediction company by angel'o'sphere · · Score: 1

    Actually we don't call it prediction, we call it prognosis.
    And there are plenty of companies like https://www.windfinder.com/ who do this since decades.

    --
    Cost free eBook I read (by iBook/Kobo/Amazon/ObookO/Gutenberg etc.): "The Green Odyssey" by Philip Jose Farmer.
    1. Re:So can any other prediction company by AHuxley · · Score: 1

      The trick in the real world is the cost of energy when wind alters and the wind turbines stop working.
      Then the energy market has to find and price in other types of energy at great cost.
      eg at night if the wind stops and the sun is not out for solar.
      Power has to stay on and has to be generated.
      A correct prediction allows for better use of energy production that can take time to set up and get ready due to complex solar and wind energy production problems.

      --
      Domestic spying is now "Benign Information Gathering"
    2. Re:So can any other prediction company by Rutulian · · Score: 1

      What you are talking about? Most weather pattern prediction services just use the NWS's GFS, including Windfinder (it even says so right in their FAQ).

      The DeepMind approach is completely different. A 36 hour forecast isn't exactly amazing, but it's just the beginning.

    3. Re:So can any other prediction company by angel'o'sphere · · Score: 1

      A correct prediction allows for better use of energy production that can take time to set up and get ready due to complex solar and wind energy production problems.
      Yes, and we work with correct prognoses since decades. My old customer EnBW, buys prognosis data from about 10 providers. The average, sometimes a weighted one, from the 3 providers that were the most accurate over the last 3 or 4 hours are used for the next hour. This is corrected every 15 minutes.
      So your feared "other power plants react to slow" scenario never happened the last 20 years ....

      --
      Cost free eBook I read (by iBook/Kobo/Amazon/ObookO/Gutenberg etc.): "The Green Odyssey" by Philip Jose Farmer.
    4. Re:So can any other prediction company by dehachel12 · · Score: 1

      You also need to take more account of surface topography.

      that really does not matter much, because for one wind turbines are erected in open wind area's, and two : they are gigantic (up to 200m as of now) and clearing all buildings and trees.

    5. Re:So can any other prediction company by Rutulian · · Score: 1

      Absolutely. And if they had done that I would have been dutifully impressed, but they didn't. They just calculated average kWh output for a block of wind turbines, which is just using the weather forecast and monitoring turbine output. I didn't realize this until I read the article more carefully (see my other comment). Small steps, I suppose....

  4. Weather Prediction is BIG MONEY by DallasTruaxxx · · Score: 1

    Imagine you are Walmart. (Insert snark here) You have one of the best distribution networks ever developed at your disposal. Your biggest problem is running out while there are still customers with money to part with when inclimate weather strikes. Knowing when and where to ship needful supplies is a huge deal because of the shipping lag. You don't have to price gouge in order to make bank, just have the stuff on hand to sell. So... if you could by reliable info from a tech company like Google, there is a price you would be willing to pay... and it's not a small number.

    1. Re:Weather Prediction is BIG MONEY by Anonymous Coward · · Score: 1

      it's more than just that. More wind means cheaper energy on the market. If you are a huge industrial electricity consumer (say, a central Walmart food distribution center) and you need to keep your freezers at least at -10F, you could go to -20F when energy is cheap, and just let it warm up to -10F while energy is more expensive. So, being able to predict wind and sun means predicting supply and demand on the energy market. If you do it well, you can save millions.

  5. I've got a question by Artem+S.+Tashkinov · · Score: 3, Insightful

    Weather forecasting is a hard mathematical problem with thousands of variables which needs to be calculated to be precise.

    The question is: does DeepMind AI/algorithm calculate the weather or it is just guessing it? If it's doing the latter then this guesswork is going to be pretty random and equally worthless, and I see no way it's gonna reach the precision of the known mathematical weather models. It might guess well in the short term (relatively few initial parameters), but in the long term I don't see it working well.

    1. Re:I've got a question by AHuxley · · Score: 1

      Decades of data, realtime weather results. What will it be over the next days? Trends over the past years? The sun?

      --
      Domestic spying is now "Benign Information Gathering"
    2. Re:I've got a question by Rutulian · · Score: 1

      It's not guessing, but it's not strictly a model-based calculation either. Wind speed and direction, in particular, is a very complex system of equations (computational fluid dynamics) that doesn't scale reasonably at all if you try to use a physical model. So the field has been trending toward statistical models and stochastic simulations for a number of years. DeepMind can effectively do both, but on steroids, and it works well because of the enormous amount of data available.

    3. Re:I've got a question by AmiMoJo · · Score: 1

      Weather forecasting is a hard mathematical problem with thousands of variables which needs to be calculated to be precise.

      That was the old way of doing it. There are limitations to that method though, because there are limits on the accuracy of measurements and problems with the vast number of hidden variables, unknown unknowns that are constantly changing.

      To get around that the old systems did a large number of predictions with random variations, and based on how like the variations were deemed to be and how many of the models resulted in high winds in area X, they would make a forecast.

      AI appears able to do a better job at this.

      --
      const int one = 65536; (Silvermoon, Texture.cs)
      SJW, n: "Someone I don't like, and by the way I'm a fuckwit" - AC
    4. Re:I've got a question by Shotgun · · Score: 1

      I would not do ANY math to make my predictions.

      There are small weather stations set up all over the place reporting in. I'd program a neural net to track down the ones that most correlate with a 36 hour prediction, and then just track those.

      Point is, I don't need a mathematically exhaustive model of the atmosphere to predict wind two days from now. I just need to look where the wind is coming from to see what's coming. When I was a kid, I learned:

      Red sun at night, sailors delight.
      Red sun in morning, sailors take warning.

      --
      Aah, change is good. -- Rafiki
      Yeah, but it ain't easy. -- Simba
  6. This works every time, until it doesn't by es330td · · Score: 1

    One year is a short timeline to declare success. This is a positive development but it will be instructive to see how this works over a multiyear period.

    1. Re:This works every time, until it doesn't by Shotgun · · Score: 1

      It'll work better over time. Each windmill will get more and more training to fine tune its specific location.

      --
      Aah, change is good. -- Rafiki
      Yeah, but it ain't easy. -- Simba
  7. Weather forecasting? by superdave80 · · Score: 1

    ...or did I miss something special about this?

    1. Re:Weather forecasting? by AHuxley · · Score: 1

      Spot price of electrical power from wind power generation.
      When to turn on gas power, state back up when wind drops.
      What new price for energy to set when wind drops, for how long and where.

      --
      Domestic spying is now "Benign Information Gathering"
  8. Oooh, goodie! by Applehu+Akbar · · Score: 1

    This means that if a calm day is predicted for tomorrow, you would know to put off running the oven and the dryer for another day.

    1. Re:Oooh, goodie! by es330td · · Score: 1

      This means that if a calm day is predicted for tomorrow, you would know to put off running the oven and the dryer for another day.

      What would in fact happen is that the wind farm, knowing it will have less power to deliver, will offer less for sale so the power grid will contract with baseload providers for the difference. What messes up electricity service is rapid and unexpected change.

  9. "trained on widely available weather forecasts" by Namarrgon · · Score: 2

    Best go direct to the source for your answers:

    Using a neural network trained on widely available weather forecasts and historical turbine data, we configured the DeepMind system to predict wind power output 36 hours ahead of actual generation.

    So no, it doesn't do weather forecasts itself, but it is based on those.

    --
    Why would anyone engrave "Elbereth"?
  10. Not wind prediction by Rutulian · · Score: 5, Informative

    Ah, ok, so I actually read the article (no I'm not new here). And it even says it right there in the summary, but somehow it didn't register. They are predicting wind power generation, not the wind itself!

    Definitely not as impressive as my first reading. They are even using existing weather forecast data, so nothing particularly innovative here. I think there is a lot of potential to do something really cool in this area with DeepMind, though. There is a ton of historical and real-time data available.

    1. Re:Not wind prediction by Rutulian · · Score: 1

      Replying to myself, but just wanted to answer the question posed in the summary:

      Is this a blow to Big Blue who purchased The Weather Channel's Weather.com to showcase Watson

      No. If this is the extent of Google's interest in this area (hopefully not), then Watson has nothing to worry about.

      , or is it news just because it's Google?

      It's not news. It's a blog post on one of Google's websites.

    2. Re: Not wind prediction by Rutulian · · Score: 1

      You've clearly never built a deep network architecture and trained it. Success is highly dependent on both domain expertise for the problem you are trying to solve, as well as a strong math and statistics background. Sure, any Joe can use TensorFlow and make a small CNN to classify their family photos, but building something that can beat world champions at Go requires teams of experts.

    3. Re:Not wind prediction by coofercat · · Score: 1

      Oh damn-it - I was hoping it could tell me when to avoid the second floor toilets :-(

  11. the big question by astrofurter · · Score: 1

    This is Google we talking about. So there's an obvious big question, now that this service has proven useful: when will they discontinue it?

  12. No one read the article by supercell · · Score: 3, Insightful
    The amount of click bait on Slashdot is getting more than I can bear. It didn't predict make a meteorological forecast ie. wind. It made "wind power predictions" by combining wind forecasts and historical wind turbine power generation data. You can do this with a simple spread sheet.

    We have been doing this for years and this is nothing new. This is news because it has Googles name in it and the AI buzz word.

    Simply astonishing what people will write up as an article and it makes as "news"

  13. Algorithms vs. models by VeryFluffyBunny · · Score: 4, Interesting

    A little lesson in scientific literacy:

    Algorithms, like Google's, that trawl through historical data & make predictions based on that work fine, as long as everything continues as before & nothing changes. It's a complex equivalent of continuing a straight line on a graph & calling it a prediction. It's completely useless & can even be destructive if you use it in combination with exerting influence on the system itself because biased or wrong predictions (which is always the case) create positive feedback loops that are self-reinforcing. A prime example of this abuse of data is so called predictive policing, which suffers from a negative form of the "Matthew Effect."

    In contrast, a theoretical model makes predictions based on the properties, forces, & constraints on a system, be it complex (probabilities) or simple (rules). Even if conditions change, anomalies appear, etc., the model is more likely to remain reasonably predictive.

    BTW, looking for patterns, regularities, etc. in data without testable hypotheses or research questions is a form of scientific malpractice called p-hacking.

    Conclusions: AI is only predictive as long as nothing changes. Models or more reliable & flexible. We shouldn't stop thinking about how the world works & give it all over to mindless algorithms.

    --
    Debate is a form of harassment. Do not question my truth.
  14. Re: If you can't predict the weather... by jouassou · · Score: 1

    Saying that you can't model the climate without an accurate prediction of the weather tomorrow, is like saying that you can't model tides without an accurate prediction of the ocean waves tomorrow.

  15. Technology Review has a nice summary... by IHTFISP · · Score: 1

    There is a concise, succinct summary at Technology Review's “The Download” page (link below):

    DeepMind’s AI is predicting how much energy Google’s wind turbines will produce

    Google’s subsidiary DeepMind has created a machine-learning model to boost the use of wind power by predicting its likely output 36 hours ahead.

    Drawbacks: Although the adoption of wind power has grown thanks to cheaper turbine costs, it will always suffer from unpredictability. That limits it compared with other energy sources that can reliably deliver power at a set time.

    An experiment: To help solve this problem, last year DeepMind started building algorithms to boost the efficacy of Google’s wind farms in the US, according to a blog post. Researchers trained a neural network on weather forecasts and past turbine data, so it could predict power output 36 hours ahead. On this basis, the model recommends how to allocate power to the grid a full day in advance. This boosted the “value” of Google’s wind farms by about 20%, DeepMind claims, though it hasn’t really specified what form what value takes, or how it’s measured.

    Implications: While it’s only been tested out internally so far, it’s not hard to imagine Google hoping to sell this technology to wind farm operators. And it’s another boost to Google’s carbon-free credentials.

    Posted by Charlotte Jee
    February 27th, 2019 7:28AM

    Ref: https://www.technologyreview.c...

    --
    Error: NSE - No Signature Error
    1. Re: Technology Review has a nice summary... by jojo50 · · Score: 1

      as hoping it could tell me when to avoid the second floor toilet https://xender.pro/ https://discord.software/ https://omegle.onl/