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I was thinking along the lines of calculating the power consumption in a given facility. I am considering the following variables:
1) Temperature, humidity - variables connected with weather
2) Occupancy, Area
3) Hour of the day,
4) Day of the week, 
5) Holiday flag, etc
I am also considering taking a few past values of consumption (Yt-1, Yt-2 etc based on auto correlation). Since the data volume is expected to be large, I am considering using the regression models rather than Arima with xreg (R might not scale up to this data). I understand it will involve ignoring the MA component. Will it be a good approach?

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A related question: could consumers be informed of the price of electricity or gas at any given time, so that they can optimize spending - for instance having a day trip in the forest when temperature is very high and use of air conditioning very expensive due to large demand? Or is price independent from demand?

No Vincent, there is not much possibility of that as we are doing this for a facility of an organization.

In my opinion regression model is good if your are getting good correlation among variables but with that you have to use ARIMA model to get future vales for all independent variable. Otherwise you can try VARIMA model which will give you benefit of both.

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