I have highly seasonal data, (it's energy consumption) with mostly 24 hour and 168 hour (=1 week) periods and I have applied differencing by 168 hours (
diff(time_series,lag=168)) to obtain something more stationary
because I don't see how I can fit any model on a series which has this many seasonalities (there is also a less obvious 12 hour period). Now I have plotted the acf and pacf and I was wondering about how to interpret these:
Lag=0 is not included because I used forecast::Acf. So on the pacf the obvious outliers are for lag=1,3 and 168.
I don't know if we can say that there is geometric or exponential decay in any of the correlograms, so any comments are welcome.