I've read about the rayleigh distribution representing the mean speed and the Kaimal Spectrum modelling the wind turbulence. But I dont really see the big picture.(adsbygoogle = window.adsbygoogle || []).push({});

I've looked through plenty of other ideas too but started with those as those are the ones that are from my notes.

I'm working on a wind turbine model but I'd like to figure this out as opposed to just getting a list of values of the wind speed taken from a site(I have found some lists on the net). However I'm not sure what to do with the formulas that come from the above models. I can see how the rayleigh distribution represents the wind with higher probabilities for the lower wind speeds and lower probabilities for the higher wind speeds. But how do I go about doing this for my model. My model of the wind turbine has an input for wind speed. So whatever I do to model the wind it must end up with a value that can be inputted to my model and over time the collective wind speed values from the random variations should look like the rayleigh distribution. Has anyone come across anything explaining this or tackled a similar problem before?

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# How does one model the wind?

Can you offer guidance or do you also need help?

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