I have much the same problem as predict-the-next-24-hours, I have several years of hourly data of demand, and I would like to predict the next 24 hours.
Ignoring the multi-seasonality issues - is it reasonable to expect the classical methods (ARIMA and ETS), to be able to forecast this much ahead?
I understand that in business scenarios, the ARIMA order is very likely to be $p+q<6$, and ETS can be paralleled with ARIMA models with even smaller p and q.
So - is it true that these models make use of the dynamics of the very last (6 or so) items in the series, and expecting them to forecast the next 24th item amounts to pure speculation? Is it possible that in a scenario like this it's better to simply aggregate the seasonal (weekly/daily) mean demand and just use that and ignore the forecasting models?