I am trying to implement an ARIMA model for my dataset. I performed a Dickey-Fuller test on my dataset and it said that it was stationary. I would like to know if the autocorrelation function can state if my dataset is stationary and how do I determine the order of my autoregressive model and moving average model from these diagrams. Also I would like to know exactly what does this autoccorelation and partial autocorrelation function say about my dataset? The last graph shows my dataset which is hourly wind speeds for 15 years.
Dickey-Fuller is not always perfect or perhaps there was an error in interpreting the results because stationary data does not produce those kinds of ACF and PACF plots. Is this data in hourly intervals? it appears there is a seasonal autocorrelation at 24 lags so you should first perform a diff(24) to remove seasonality and then maybe one more first order diff to remove trend and check out correlation plots again.
Choosing your ARIMA orders is a bit of an art. I would point you to this resource for a good place to start: https://otexts.org/fpp2/arima-r.html