I work in a closely related space: parent's comments are accurate. Some of these items can be solved with better forecasting models, but the issue is that almost no-one actually cares about 'better' forecasting at inidividual meter levels. Sysytem-wide (or at least substation level) forecasts are well studied for supply/demand considerations (at a minimum). Also, the variability in consumption patterns at an individual level are large. IOW, one might be able to generate forecasts accurately for 'typical' residential consumption (at a per-household level), but commercials can be very different.
Ideally, IF (and this is a BIG if), forecasts for "most" premises was accurate enough, then one could make the claim that the missing data shouldnt really cause a recalculation of bill once the actual consumption data comes thru, except in cases where the error is large. Guess that means that the error check/correct process needs to continue to exist.
The meter being replaced shouldnt be a major issue, this is relational (at least we treat this all as relational) data that should be captured (by the customer information 'CIS' system), and should be available with a 1-2 day delay. Similar argument applies to other relational aspects of the premise under consideration. Not saying that those are easy (more ways for this process to have gaps).
The meter being replaced shouldnt be a major issue, this is relational (at least we treat this all as relational) data that should be captured (by the customer information 'CIS' system), and should be available with a 1-2 day delay. Similar argument applies to other relational aspects of the premise under consideration. Not saying that those are easy (more ways for this process to have gaps).