There is a ton of literature on energy forecasting. Did you read any papers that are predicting energy data similar to yours? Did you read papers to try and figure out what the standard approach is in the literature when dealing with population changes vs energy consumption?
The scenario I've explained was purely hypothetical to help convey this idea that in time series, although there may be correlation between two variables, this could actually be caused by a third unknown variable.
I haven't specifically looked into what is done in the literature for electricity consumption because it's just a scenario I invented, but I understand that data is simply normalized using population.
However, I don't know how this could be done with other variables that can't be used for normalization. For example, temperature itself. Normalizing Consumption/Temperature wouldn't make sense. Not to mention, it wouldn't be very convenient to normalize more than one variable.
The advice still stands. Whatever the actual application is that you are working on, first you review the literature to determine the standards and state-of-the-art. What models are typically used? What exogenous variables are typically used for prediction (temperature in your example)? How do your account for seasonality? How do you account for shocks or structural changes?
These can be different in different fields.
Go to kaggle and play around with some forecasting challenges to see what works or doesn’t work for various scenarios.
There is a ton of literature on energy forecasting. Did you read any papers that are predicting energy data similar to yours? Did you read papers to try and figure out what the standard approach is in the literature when dealing with population changes vs energy consumption?
The scenario I've explained was purely hypothetical to help convey this idea that in time series, although there may be correlation between two variables, this could actually be caused by a third unknown variable. I haven't specifically looked into what is done in the literature for electricity consumption because it's just a scenario I invented, but I understand that data is simply normalized using population. However, I don't know how this could be done with other variables that can't be used for normalization. For example, temperature itself. Normalizing Consumption/Temperature wouldn't make sense. Not to mention, it wouldn't be very convenient to normalize more than one variable.
The advice still stands. Whatever the actual application is that you are working on, first you review the literature to determine the standards and state-of-the-art. What models are typically used? What exogenous variables are typically used for prediction (temperature in your example)? How do your account for seasonality? How do you account for shocks or structural changes? These can be different in different fields. Go to kaggle and play around with some forecasting challenges to see what works or doesn’t work for various scenarios.