Looks like they did some pretty comprehensive testing:
> "In a months-long experiment in a real utility-scale wind farm in India, the predictive model was first validated by testing a wide range of yaw orientation strategies, most of which were intentionally suboptimal. By testing many control strategies, including suboptimal ones, in both the real farm and the model, the researchers could identify the true optimal strategy. Importantly, the model was able to predict the farm power production and the optimal control strategy for most wind conditions tested, giving confidence that the predictions of the model would track the true optimal operational strategy for the farm. This enables the use of the model to design the optimal control strategies for new wind conditions and new wind farms without needing to perform fresh calculations from scratch."
There are definitely a number of installations where this could be useful. My favorite example is Antelope Valley in Southern CA, where the turbines stretch out as far as the eye can see. The scale is absurd. 3288 turbines are there, according to https://eros.usgs.gov/media-gallery/earthshot/wind
The 1.2٪ figure was a month long average from a real-world test. In certain conditions they got 32% higher efficiency. Presumably those are the conditions when the wind is blowing sub-optimally.
Unrelatedly, from personal experience both onshore and offshore windfarms seem to be packed much tighter than in a line.
Wind farms in my state have grids of towers across square miles. So nearly every tower is in the 'wind shadow' of any number of other towers. This seems like a very suitable innovation here.
What about when the wind is tangent to installation line and blowing across them. Wouldn't they all rotate to face the wind and now be in front of one another?
"But in the new system, for example, the team has found that by turning one turbine just slightly away from its own maximum output position — perhaps 20 degrees away from its individual peak output angle — the resulting increase in power output from one or more downwind units will more than make up for the slight reduction in output from the first unit."
I assume that this could also increase the speed of a cooperative convoy of sailboats, that have a good reason to stay close. I wonder if the fleets of sailing ships of Admiral Nelson's time took advantage of this. A few extra ergs of force in a sea chase could make a large difference.
The idea here is 'stay out of dirty air better'. It isn't a real gain for the downwind turbines, just less of a loss.
This concept has long been known to sailors. And I presume that sailing in convoys took this effect of dirty air well into account.
You see this in competitive dinghy racing. One person will intentionally starve their competitor of good air, so they know and could do the opposite if they wanted.
Lots of sports deal with this “dirty air” concept like Formula 1 especially, regulations were changed for this season so the car in front produces cleaner air off the back so cars behind can follow better (which provides a better chance to overtake/better viewing spectacle).
Using global control instead of local control seems like such an obvious improvement that I wonder why it hasn't been used earlier. I wonder whether the real difficulty lies in getting the simulations accurate enough to make useful predictions.
As the old say, the devil lies in details. Writing a global control is no means an easy task, as
1. You need to recognize the opportunities exist in the first place.
2. You need a global controller that can aggregate and optimize for a global solution (and the global solution might not necessarily simply to maximize the aggregate throughput, but there might be other factors into account), which may involve some algorithmic design (in some cases, you need to design new algorithms).
3. You need to justify that global controller gives you a superior solution compared to locally greedy solution. As in this article, a global solution gives you about 3% improvement compared to the local controller, and the local controller algorithm is substantially easier to write.
Background: in my previous job at Meta, I wrote such a global control algorithm for controlling the rate of data going in and out each data center. It involved some really interesting algorithmic design.
It has been done earlier; multiple times, by every serious manufacturer. :-]
The real difficulty lies in:
1) Noise in the on-turbine wind speed and direction measurements and/or robustly (see point #2) operating LIDAR or met masts in front of the farm to try to avoid said measurement noise.
2) Actually arriving at a robust, operational in real-world conditions, fully closed-loop control system. A commercial wind farm has to operate 24/7 for 25 years without a bunch of engineers and scientists babysitting it, which is what is likely to end up happening if the cool control system relies on offline simulation results, topographical data, and/or human-supervised calibration & tuning.
It's not all doom and gloom: Ongoing improvements in sensor price/quality will probably make these kind of global control systems more and more practically feasible in the future.
It's a 1.2% overall improvement. That's the kind of number where it's worth doing in general, and worth using if it's been developed, but not nearly worth the development effort and headache for a wind farm operator trying to invent it on their own.
considering it amounts to 1.2% over a period, I wouldn't say "obvious improvement"
local maximizing presumably already deals with the effects from upstream turbines, global (also presumably) only adds consideration for downstream turbines
Why are wind turbines constructed like reverse propellers?
Would they not be more efficient if they were shaped like an actual turbine with a deep spiraling blade, placed inside a cylindrical or conical encasing?
This is a really good question. The reason regular turbines and wind turbines are designed differently is because regular turbines have a small volume of fluid experiencing a large change in pressure while wind turbines have a large volume of fluid experiencing a small change in pressure. You see the exact same thing in fans - big ceiling fans look like wind turbines and air compressors look a lot like regular turbines.
I’m sure the cost of a casing plays into it, but its primarily about the energy efficiency of different blade shapes in different hydraulic conditions.
There's a bunch of maths around Betz' law that dictates how the efficiency works, but it turns out that the theoretically optimal structure is a single blade: http://www.wind-works.org/cms/index.php?id=543
For mechanical engineering reasons, mostly to do with evening out the load at the point of blade attachment, the industry has mostly converged on three.
Remember that the blades are aerofoils, effectively wings. They don't need to touch all the air in their swept area, their effect is given by redirecting the flow of the whole stream of air.
Casings are only useful for small turbines operating at high pressures, where the energy lost to spilling over the tip of the blade would be high.
You've already received some good responses (particularly from /u/pjc50), but one particular point may not be real clear.
Generally speaking, the power a wind turbine can generated is proportional to the entire swept area. So, other things being equal, it is better to go for longer blades to increase the area, rather than trying to "capture all the wind" in a smaller cross-sectional area.
So the most efficient use of your wind turbine's mass (which is proportional to cost) is to make it as big as feasible.
For the same reason propellers aren't shaped like compressor blades inside a cylindrical encasing. The cylindrical encasing dramatically reduces air flow, but is necessary for large pressure changes. For a brayton cycle heat engine, like a jet engine, you need to maximize pressure gradient for optimal efficiency, but if you're not burning fuel then you want to minimize pressure gradient and maximize mass flow rate.
I believe that if you consider the money it takes to add the conical casing, and instead just make a bigger tri-blade without a casing with that same money, you come out ahead.
Interesting development, but quite a few of these concerns are normally dealt with during wind park development and siting, taking care of the 'wake effect' in the prevailing wind with all machines operating is pretty much standard. The upside of this - if I understand it correctly - is that it will try to find another optimum when the wind is not from the 'ideal' direction that the park was originally designed for. So it will depend very much on how variable the winds are in a particular locality whether this will give an advantage.
I'm curious how it will play out in practice when they start using it on large offshore installations for instance.
Cool. We have worked with a customer on this exact thing and deployed an edge and cloud controller that orchestrates control changes based on the all the turbines. Such a great project!
Serious question here. Why I see all these breakthroughs coming from MIT? Are they really heads and shoulders above everyone else or do they have great PR/marketing?
If you look at the paper it's actually a collaboration between MIT researchers, Caltech researchers, a Spanish Siemens groups, and an Indian power company.
MIT just has a more effective marketing division, it seems. Here's the Caltech press release for comparison.
> "Collectively, wind farms generate about 380 billion kilowatt-hours each year in the United States. If every U.S. wind farm were to adopt the new strategy and see efficiency increases similar to those found in the new study, it would be equivalent to adding hundreds of new turbines capable of powering hundreds of thousands of homes to the nation's power grid, says Caltech's John O. Dabiri (MS '03, PhD '05), the Centennial Professor of Aeronautics and Mechanical Engineering, and senior author of a paper on the project that was published by the journal Nature Energy on August 11."
At least in this case, it seems that MIT is only tangentially related to the research. The lead researchers are from Spain and India with financing from Siemens.
Probably both, it is a top research university in the world, with a lot of smart people and funding. Also note the "T" in MIT stands for technology, they do tend to focus a bit more on practical applications and not just theoretical knowledge.
Its good marketing and I would keep an eye on what accounts are submitting these. Its practically a trope on HN at this point. Not to say that MIT doesn't do cool stuff, but there are few institutions as good at self promotion.
In addition to the other replies, it's also worth mentioning that they have an incredibly large endowment, worth $27.4 billion last year, the fifth largest of any private university in the US. That's compared to an average of $1.1 billion, and a median of just $200 million, less than 1% of MIT's.
> Virtually all wind turbines, which produce more than 5 percent of the world’s electricity, are controlled as if they were individual, free-standing units.
I refuse to believe this, every wind engineer would know one windmill affects the next.
Its not as clear as the picture either where they are lined up. In most locations wind changes direction so for some flows they'll interact different to others.
Wind engineers know this, but the software control work is non trivial and, apparently, simply hasn't been done.
A few years ago I was talking with a family member who is in wind power research. They were trying to convince me to start writing turbine control software because it is massively inefficient and naive.
I was shocked at some of the optimizations they are lacking.
This makes me wonder if it could be optimized further if mechanical design changes are explored. It's common practice in aerospace to minimize dirty air in certain cases. I wonder if there are opportunities where different turbine designs could be deployed depending on the windmill density.
The research was definitely worth pursing. A 1.2% overall efficiency gain is not nothing, and is indeed significant enough that I think people will want to implement it.
On the other hand, without doing some extensive research, it wasn't clear what the magnitude of the improvement actually was.
[+] [-] koheripbal|3 years ago|reply
Often, wind turbines are arranged in a line across the usual wind front, so turbulence isn't typically an issue.
So, in this case, when wind passes over multiple nearby turbines serially, then there is a 1.2% gain on efficiency.
Still a worthwhile deployment if the model is accurate. Needs to be tested.
[+] [-] photochemsyn|3 years ago|reply
> "In a months-long experiment in a real utility-scale wind farm in India, the predictive model was first validated by testing a wide range of yaw orientation strategies, most of which were intentionally suboptimal. By testing many control strategies, including suboptimal ones, in both the real farm and the model, the researchers could identify the true optimal strategy. Importantly, the model was able to predict the farm power production and the optimal control strategy for most wind conditions tested, giving confidence that the predictions of the model would track the true optimal operational strategy for the farm. This enables the use of the model to design the optimal control strategies for new wind conditions and new wind farms without needing to perform fresh calculations from scratch."
[+] [-] timerol|3 years ago|reply
Streetview: https://www.google.com/maps/@35.0385954,-118.2567896,3a,75y,...
[+] [-] rocqua|3 years ago|reply
Unrelatedly, from personal experience both onshore and offshore windfarms seem to be packed much tighter than in a line.
[+] [-] JoeAltmaier|3 years ago|reply
[+] [-] fastest963|3 years ago|reply
[+] [-] hirundo|3 years ago|reply
I assume that this could also increase the speed of a cooperative convoy of sailboats, that have a good reason to stay close. I wonder if the fleets of sailing ships of Admiral Nelson's time took advantage of this. A few extra ergs of force in a sea chase could make a large difference.
[+] [-] rocqua|3 years ago|reply
[+] [-] scrivna|3 years ago|reply
[+] [-] adrianN|3 years ago|reply
[+] [-] linhvn|3 years ago|reply
1. You need to recognize the opportunities exist in the first place.
2. You need a global controller that can aggregate and optimize for a global solution (and the global solution might not necessarily simply to maximize the aggregate throughput, but there might be other factors into account), which may involve some algorithmic design (in some cases, you need to design new algorithms).
3. You need to justify that global controller gives you a superior solution compared to locally greedy solution. As in this article, a global solution gives you about 3% improvement compared to the local controller, and the local controller algorithm is substantially easier to write.
Background: in my previous job at Meta, I wrote such a global control algorithm for controlling the rate of data going in and out each data center. It involved some really interesting algorithmic design.
[+] [-] convFixb|3 years ago|reply
The real difficulty lies in:
1) Noise in the on-turbine wind speed and direction measurements and/or robustly (see point #2) operating LIDAR or met masts in front of the farm to try to avoid said measurement noise.
2) Actually arriving at a robust, operational in real-world conditions, fully closed-loop control system. A commercial wind farm has to operate 24/7 for 25 years without a bunch of engineers and scientists babysitting it, which is what is likely to end up happening if the cool control system relies on offline simulation results, topographical data, and/or human-supervised calibration & tuning.
It's not all doom and gloom: Ongoing improvements in sensor price/quality will probably make these kind of global control systems more and more practically feasible in the future.
[+] [-] a_shovel|3 years ago|reply
[+] [-] asojfdowgh|3 years ago|reply
local maximizing presumably already deals with the effects from upstream turbines, global (also presumably) only adds consideration for downstream turbines
[+] [-] rocqua|3 years ago|reply
Local control, and no need for a global coordinator, might be so much simpler as to be worth losing some efficiency / not going into integration hell.
[+] [-] lizardactivist|3 years ago|reply
Would they not be more efficient if they were shaped like an actual turbine with a deep spiraling blade, placed inside a cylindrical or conical encasing?
[+] [-] elil17|3 years ago|reply
I’m sure the cost of a casing plays into it, but its primarily about the energy efficiency of different blade shapes in different hydraulic conditions.
[+] [-] pjc50|3 years ago|reply
For mechanical engineering reasons, mostly to do with evening out the load at the point of blade attachment, the industry has mostly converged on three.
This is also linked to tip speed ratio: http://www.reuk.co.uk/wordpress/wind/wind-turbine-tip-speed-... ; the tip speed is usually several times faster than the wind speed.
Remember that the blades are aerofoils, effectively wings. They don't need to touch all the air in their swept area, their effect is given by redirecting the flow of the whole stream of air.
Casings are only useful for small turbines operating at high pressures, where the energy lost to spilling over the tip of the blade would be high.
[+] [-] ansible|3 years ago|reply
Generally speaking, the power a wind turbine can generated is proportional to the entire swept area. So, other things being equal, it is better to go for longer blades to increase the area, rather than trying to "capture all the wind" in a smaller cross-sectional area.
So the most efficient use of your wind turbine's mass (which is proportional to cost) is to make it as big as feasible.
[+] [-] jjk166|3 years ago|reply
[+] [-] timbit42|3 years ago|reply
[+] [-] jackmott42|3 years ago|reply
[+] [-] jacquesm|3 years ago|reply
I'm curious how it will play out in practice when they start using it on large offshore installations for instance.
[+] [-] jordz|3 years ago|reply
[+] [-] jmartrican|3 years ago|reply
[+] [-] photochemsyn|3 years ago|reply
MIT just has a more effective marketing division, it seems. Here's the Caltech press release for comparison.
https://www.caltech.edu/about/news/tweaking-turbine-angles-s...
> "Collectively, wind farms generate about 380 billion kilowatt-hours each year in the United States. If every U.S. wind farm were to adopt the new strategy and see efficiency increases similar to those found in the new study, it would be equivalent to adding hundreds of new turbines capable of powering hundreds of thousands of homes to the nation's power grid, says Caltech's John O. Dabiri (MS '03, PhD '05), the Centennial Professor of Aeronautics and Mechanical Engineering, and senior author of a paper on the project that was published by the journal Nature Energy on August 11."
[+] [-] gostsamo|3 years ago|reply
[+] [-] marktangotango|3 years ago|reply
[+] [-] RosanaAnaDana|3 years ago|reply
[+] [-] jehb|3 years ago|reply
Source: https://www.insidehighered.com/news/2022/02/18/college-endow...
[+] [-] linhvn|3 years ago|reply
[+] [-] rr888|3 years ago|reply
I refuse to believe this, every wind engineer would know one windmill affects the next.
Its not as clear as the picture either where they are lined up. In most locations wind changes direction so for some flows they'll interact different to others.
[+] [-] calt|3 years ago|reply
A few years ago I was talking with a family member who is in wind power research. They were trying to convince me to start writing turbine control software because it is massively inefficient and naive.
I was shocked at some of the optimizations they are lacking.
[+] [-] zeristor|3 years ago|reply
It has been standard practice in most industries to co-opt any improvement into increasing the company’s stickiness.
It would be a shame if it did.
[+] [-] deelowe|3 years ago|reply
[+] [-] mhb|3 years ago|reply
[+] [-] ansible|3 years ago|reply
The research was definitely worth pursing. A 1.2% overall efficiency gain is not nothing, and is indeed significant enough that I think people will want to implement it.
On the other hand, without doing some extensive research, it wasn't clear what the magnitude of the improvement actually was.
[+] [-] Silverback_VII|3 years ago|reply