I'm working on a project, trying to model electricity consumption and generation from a bunch of PV generators to see how much of the demand can be satisfied by the production in the "town". Most models use a fixed demand and production profile in an hourly time-series.
I'd like to see how variations in both production and demand would influence the outcome. So basically a Monte Carlo simulation of the whole system.
Is there a relatively easy way to vary a given demand and production profile with a sort of random factor? Obviously the diurnal and annual variations should still be similar to the "measured" dataset.
I played around with something called Iterative Amplitude Adapted Fourier Transform, but the variations are totally out of whack (maybe because I didn't adjust the parameters correctly). Sadly my education in statistics is not very deep.
Thanks for any suggestion!