Submitted by Barra79 t3_11i5hv3 in dataisbeautiful
Comments
Reelplayer t1_jawmtmc wrote
Wouldn't the real data be generation at a single turbine related to wind speed? Energy generated by wind throughout an entire country is kind of useless information without the context of what went into creating that source and what it takes to maintain it.
ButterflyCatastrophe t1_jawve0q wrote
It depends what you're trying to show. Wind speed vs power for a single turbine is just physics. Weight all of the local wind speeds by the number of turbines on the grid, and you'd get a more precise national estimate. Based on OP's comments, I'd guess that a lot of Germany's wind power comes from Bremen.
OP has produced a bunch of 'some kind of marker for windy day' against 'power from various sources.' The set lets you tell that wind substitutes for petroleum, presumably because gas and oil plants are more dynamic than nuclear or coal. It seems like he's picked a city that's reasonably representative and accessible to humans, rather than a complicated formula that might be more predictive but not useful to readers. It gives the impression that there's got to be a pretty good wind blowing before you get much out of wind.
Might be helpful to have a histogram of wind speed at the bottom, so reader can get some sense of how often wind power is a significant factor.
[deleted] t1_jaxwoeo wrote
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MattOfMatts t1_jawt9nu wrote
Averages are fine but the power grid also cannot run on averages. You need supply to equal demand at all times. The spread on this chart is very large, with 10-20GW of difference for any given wind speed.
So while your math is fair, the application of it seems somewhat pointless. It does the grid no good that the average of wind is a certain value, instead the real time value is all that really matters.
Either we invest in more the storage or raise the amount of wind production to raise the lowest minimums, then the math changes. but then the outliers become more critical in analyzing, because failure to account for all outliers results in loss of power.
Lambylambowski t1_jawtmjh wrote
Wind does blow in only one place and never changes speed so, this checks out.
johnnyGotHisTabla t1_jaylx5g wrote
>Instead it can be argued that if it's calm in Hamburg it is still very likely that it is windy in many other parts of Germany
The industry way to capture this is with a portfolio benefit analysis.
I don't know how safe your assumption is in Germany.
I am far more familiar with wind regimes in the States. If you have a plant in northern Texas, another in Iowa, another in the Columbia River valley in Oregon, and the last in Tehachapi pass in Cali, you have a full portfolio benefit lol
Barra79 OP t1_jaxc48e wrote
Here's the same graph for just Offshore: https://imgur.com/gXTKRg4
And using Borkum, which is an island on the West coast:https://imgur.com/a/GNR2M9c
geek66 t1_jaxdtun wrote
This one makes a little more sense to me, I would expect max power to be at lower speed than the original Germany based plot, and the decreasing power at high wind speed as they go offline and “park”
mfb- t1_jazsc80 wrote
OP is the total production in Germany, extremely windy conditions in Hamburg will usually come with less extreme winds elsewhere.
geek66 t1_jb0j5ut wrote
Exactly my point, so it dilutes the data, and gives misleading impression.
in_taco t1_jb0t9k1 wrote
Wind turbines derate earliest from 20 m/s and cut out around 30-40 m/s. On this graph it drops off at 14 m/s, so it doesn't fit.
Also I hate seeing powercurves in km/h. Nobody does that in the wind industry.
geek66 t1_jb0wcbc wrote
Point being, the original post did not reflect this behavior at all.
holgerschurig t1_jb3t37v wrote
Why not, it's SI units. Everyone (in europe) knows km/h and has a pretty good picture of it, e.g. from driving. So the selected units meets the intended audience.
I hate the "knots" or other measures. They should perhaps switch from BS units to SI units.
in_taco t1_jb3tcso wrote
Because you're plotting what's called a "powercurve". It's a standard figure in the wind industry, because wind is nearly always measured in m/s or knots.
I've worked with wind turbines for 11 years and made hundreds of powercurves. Never seen anyone use km/h before.
pierebean t1_jaxo8g1 wrote
For taller turbines you need wind lidar (like windcubes) to measure the wind speed.
jimtoberfest t1_jaxra73 wrote
This. +1. The wind speed is not uniform across the disc area of turbines. You need wind speed at several points in height. Although not sure what OP is really trying to determine here just avg power v wind speed but fit looks poor at lower end.
johnnyGotHisTabla t1_jayllr7 wrote
> The wind speed is not uniform across the disc area of turbines.
Depending somewhat on the time of day (or really: night)
RenegadeMoose t1_jaxre3x wrote
Dumb question, but why is the red line between 10km/h and 20km/h plotted so much higher above the dense mass of dots below it?
Shouldn't the red line be coming in a bit lower and angling up a bit steeper along that part of the graph?
( or are all those low-density outliers above the red line causing it to appear higher up? )
Kualityy t1_jb0d62m wrote
>or are all those low-density outliers above the red line causing it to appear higher up?
Pretty much this. Least squares regression is sensitive to outliers.
Barra79 OP t1_jaxsay9 wrote
Im using a poly fit function set to the third degree: https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html
KiwasiGames t1_jaykfef wrote
Check your residuals. A third degree polynomial doesn’t look particularly appropriate here.
VikThorior t1_jb22gkq wrote
As I said below another post you made, don't do a regression if you don't have a model in mind. It may just be hypothetical, but you must have an explanation as to why you chose this regression in particular, other than "it fits pretty well". A 100th degree polynomial function will fit better, a Ngh degree polynomial, with N the number of points, will fit perfectly.
Also, the problem you have here is that you have "positive" outliers but you don't have negative outliers for the lowest values, because energy production can't go below 0. So you have a regression which is higher than the truth. You should find a way to identfy and eliminate these outliers.
And if you can't that's not a problem! We don't need a regression all the time. We see the relationship pretty well, the red line is not needed. It just shows a model which is obviously wrong for many reasons.
RenegadeMoose t1_jaxtf0m wrote
Thanks! Like I said, "dumb question" but I had to ask :)
Barra79 OP t1_jawibyn wrote
Wind Power Source: https://www.entsoe.eu/ ENTSOE API. Summing onshore and offshore values for Germany.
Wind Speed Source: https://open-meteo.com/ Open-meteo API, taking the wind speed in Hamburg Germany at a height of 80m.
kyrsjo t1_jb09rc0 wrote
I was wondering how you got the data, and that open-meteo thing is extremely interesting for getting historical data.
Last time i looked at this, which is about 5 years ago, the solution proposed to me by friends in climate science was to download datasets for testing climate models, and extract (very rough resolution) it from there. Or you could buy observational data from a meteo service for way too much money.
Bookmarked!
Rotlam t1_jaxdfu6 wrote
It seems like there's a lot of noise at the bottom-left of these distributions. It might be interesting to see if the top end of the noise is preceded by higher wind speeds/power generation or follows it.
Barra79 OP t1_jaxdsye wrote
Can you provide an x,y coordinate to better describe where on the map you mean please?
Rotlam t1_jaxj0yu wrote
Oh sure. My intuition is that wind speeds below the line of best fit (in the area of 2.5 GW from 5 km/h to 15 km/h) are below the line of best fit because the fan blades were slower (or zero) and don't operate well at low speeds.
Meanwhile the power generation of about 20 GW and ~14GW between 10 and 20 km/h might be because they had slowed down from a previous high point.
Barra79 OP t1_jaxrggl wrote
Yeah the wind turbines dont produce electricity until they reach their cut in speed which is around 15 to 20km/h I believe. Then they have a max output, somewhere around 55km/h. They also need to park at high wind speeds or risk getting damaged. You can see this more clearly here: https://imgur.com/a/GNR2M9c
sploogmcduck t1_jazzr3b wrote
This would mean a single fit is innappropriate to describe the data.
[deleted] t1_jaxzt3h wrote
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uioreanu t1_jazdxk3 wrote
Can we have a similar chart for PV ? Light x Temperature
theD0UBLE t1_jb0aqob wrote
Is Betz limit still considered accurate? Cause the data looks to go with it.
SunnyDayInPoland t1_jb0jyzj wrote
Yes, I think we're as likely going faster than the speed of light as we are beating the Betz limit
uchunokata t1_jb0ery4 wrote
The turbines are designed to handle specific wind speed ranges. So once you get outside the design envelope you are going to get little to no power generation.
tgiccuwaun t1_jb0g57d wrote
How would you normalize this to factor in demand? Lots of windy days where there is no demand and also windless days with high demand. Wind speed and peak demand aren't correlated.
ApprehensiveSorbet76 t1_jb0wra6 wrote
It’s important to note that potential power increases with the cube of velocity, but too much power means the forces are so high that it’s impossible to keep the system from self destructing.
So the curve plateaus because the turbines purposefully puts on the brakes to limit power. And at some point the wind will be so strong that the turbine is completely shut down.
If a turbine were capable of operating at full power under 100km/hr winds, the output would be spectacular.
CamperStacker t1_jaxpvb2 wrote
Now they just need to invent a light bulb that lights in proportion with how much wind is blowing.
useibeidjdweiixh t1_jaxy1pr wrote
This isn't how such data is displayed. The wind industry uses SI units, m/s for wind speed. What's the red line representing? For normal power curves for turbines it would be the warranted power values from the OEM. It's a decent idea but the data is too noisy to properly show the correlation. It doesn't look like a strong correlation from the graph when wind speed cubed is directly correlated to power.
[deleted] t1_jaym3ax wrote
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Barra79 OP t1_jawicfu wrote
I'd like to explain why I am only taking the wind speed in Hamburg. Based on my graph, I believe it is reasonable for someone in Hamburg to argue that if it is not windy there at a given time, then it is very unlikely that Germany as a whole is generating much in the way of electricity from Wind Power. However, if I average out the wind in Germany to produce this graph, then no such claim can be made. Instead it can be argued that if it's calm in Hamburg it is still very likely that it is windy in many other parts of Germany, resulting in lots of Wind Power anyway. Furthermore, if I produce the above graph for Bremen, I get a very similar correlation. So a person in Bremen can make a similar claim as that mentioned above for Hamburg. With regard to Berlin, the correlation is still clear, but not a tight as above.
Bremen: https://imgur.com/a/aahs9Vm
Berlin: https://imgur.com/a/LgTFNiV
Cologne: https://imgur.com/mcc8IYC