AnsweredAssumed Answered

Roll Up Analysis

Question asked by Koerkel on Nov 5, 2018
Latest reply on Nov 7, 2018 by Koerkel

I have two different types of meters; one measuring at 15 minute intervals and the other measuring at 60 minute intervals.  I want to sum the measurement up to the transformer (the parent).  I found that if I do a standard roll up analyses, PI wants to interpolate values on each quarter hour for the hourly meters.  Thus my rollup value was higher than the actual sum from the meters.  I corrected this by adding a PI point to my 15 minute meters to sum the entire hour to the ordinal hour thus faking my 15 minute meters to look as if they were hourly meters.  Here is the analysis I used:

if Minute('*')<>0 then NoOutput() 

else TagMean('Wh Delivered Int Raw value', '*-50m', '*') * EventCount('Wh Delivered Int Raw value', '*-50m', '*')*'CTPTRatio'/1000

 

For my hourly meters I simply converted the raw measurement into the proper units as so:

'Wh Delivered Int Raw value'*'CTPTRatio'/1000

I then sum the values from these analyses to obtain the hourly summed value.  This works for the most part, however, I am still receiving 96 values per day on my transformer when I expected 24 values. The values on the each quarter of the hour equals the values summed to the previous ordinal hour.  How can I roll up the measurements and only have 24 values?  Here is a simple example of what my data looks like:

 

      

Meter summed to the hour and converted to KWH Meter Raw data in WH
Transformer A
Wh Load
Meter 1
kWh Delivered Interval
Meter 1
Wh Delivered Int Raw value
Number of Values:96Number of Values:24Number of Values:96
10/31/2018 0:150.50810/31/2018 1:000.5110/31/2018 0:15128
10/31/2018 0:300.50810/31/2018 2:000.5110/31/2018 0:30129
10/31/2018 0:450.50810/31/2018 3:000.51510/31/2018 0:45126
10/31/2018 1:000.5110/31/2018 4:000.51610/31/2018 1:00127
10/31/2018 1:150.5110/31/2018 5:000.50810/31/2018 1:15127
10/31/2018 1:300.5110/31/2018 6:000.50210/31/2018 1:30128
10/31/2018 1:450.5110/31/2018 7:000.49810/31/2018 1:45127
10/31/2018 2:000.5110/31/2018 8:000.49210/31/2018 2:00128
10/31/2018 2:150.5110/31/2018 9:000.49810/31/2018 2:15128
10/31/2018 2:300.5110/31/2018 10:000.49810/31/2018 2:30129
10/31/2018 2:450.5110/31/2018 11:000.49510/31/2018 2:45129
10/31/2018 3:000.51510/31/2018 12:000.49810/31/2018 3:00129
10/31/2018 3:150.51510/31/2018 13:000.50410/31/2018 3:15130
10/31/2018 3:300.51510/31/2018 14:000.510/31/2018 3:30129
10/31/2018 3:450.51510/31/2018 15:000.50610/31/2018 3:45129
10/31/2018 4:000.51610/31/2018 16:000.51410/31/2018 4:00128
10/31/2018 4:150.51610/31/2018 17:001.32910/31/2018 4:15129
10/31/2018 4:300.51610/31/2018 18:002.69910/31/2018 4:30127
10/31/2018 4:450.51610/31/2018 19:002.76910/31/2018 4:45127
10/31/2018 5:000.50810/31/2018 20:002.81210/31/2018 5:00125
10/31/2018 5:150.50810/31/2018 21:002.85410/31/2018 5:15126
10/31/2018 5:300.50810/31/2018 22:002.88810/31/2018 5:30125
10/31/2018 5:450.50810/31/2018 23:002.85810/31/2018 5:45126
10/31/2018 6:000.50211/1/2018 0:002.77910/31/2018 6:00125
10/31/2018 6:150.502 10/31/2018 6:15124
10/31/2018 6:300.502 10/31/2018 6:30124
10/31/2018 6:450.502 10/31/2018 6:45125
10/31/2018 7:000.498 10/31/2018 7:00125
10/31/2018 7:150.498 10/31/2018 7:15123
10/31/2018 7:300.498 10/31/2018 7:30123
10/31/2018 7:450.498 10/31/2018 7:45123
10/31/2018 8:000.492 10/31/2018 8:00123
10/31/2018 8:150.492 10/31/2018 8:15125
10/31/2018 8:300.492 10/31/2018 8:30124
10/31/2018 8:450.492 10/31/2018 8:45124
10/31/2018 9:000.498 10/31/2018 9:00125
10/31/2018 9:150.498 10/31/2018 9:15125
10/31/2018 9:300.498 10/31/2018 9:30124
10/31/2018 9:450.498 10/31/2018 9:45124
10/31/2018 10:000.498 10/31/2018 10:00125
10/31/2018 10:150.498 10/31/2018 10:15123
10/31/2018 10:300.498 10/31/2018 10:30124
10/31/2018 10:450.498 10/31/2018 10:45124
10/31/2018 11:000.495 10/31/2018 11:00124
10/31/2018 11:150.495 10/31/2018 11:15124
10/31/2018 11:300.495 10/31/2018 11:30124
10/31/2018 11:450.495 10/31/2018 11:45124
10/31/2018 12:000.498 10/31/2018 12:00126
10/31/2018 12:150.498 10/31/2018 12:15127
10/31/2018 12:300.498 10/31/2018 12:30127
10/31/2018 12:450.498 10/31/2018 12:45125
10/31/2018 13:000.504 10/31/2018 13:00125
10/31/2018 13:150.504 10/31/2018 13:15125
10/31/2018 13:300.504 10/31/2018 13:30125
10/31/2018 13:450.504 10/31/2018 13:45125
10/31/2018 14:000.5 10/31/2018 14:00125
10/31/2018 14:150.5 10/31/2018 14:15126
10/31/2018 14:300.5 10/31/2018 14:30126
10/31/2018 14:450.5 10/31/2018 14:45126
10/31/2018 15:000.506 10/31/2018 15:00128
10/31/2018 15:150.506 10/31/2018 15:15128
10/31/2018 15:300.506 10/31/2018 15:30129
10/31/2018 15:450.506 10/31/2018 15:45128
10/31/2018 16:000.514 10/31/2018 16:00129
10/31/2018 16:150.514 10/31/2018 16:15129
10/31/2018 16:300.514 10/31/2018 16:30204
10/31/2018 16:450.514 10/31/2018 16:45400
10/31/2018 17:001.329 10/31/2018 17:00596
10/31/2018 17:151.329 10/31/2018 17:15673
10/31/2018 17:301.329 10/31/2018 17:30671
10/31/2018 17:451.329 10/31/2018 17:45673
10/31/2018 18:002.699 10/31/2018 18:00682
10/31/2018 18:152.699 10/31/2018 18:15689
10/31/2018 18:302.699 10/31/2018 18:30691
10/31/2018 18:452.699 10/31/2018 18:45693
10/31/2018 19:002.769 10/31/2018 19:00696
10/31/2018 19:152.769 10/31/2018 19:15699
10/31/2018 19:302.769 10/31/2018 19:30700
10/31/2018 19:452.769 10/31/2018 19:45705
10/31/2018 20:002.812 10/31/2018 20:00708
10/31/2018 20:152.812 10/31/2018 20:15711
10/31/2018 20:302.812 10/31/2018 20:30712
10/31/2018 20:452.812 10/31/2018 20:45715
10/31/2018 21:002.854 10/31/2018 21:00716
10/31/2018 21:152.854 10/31/2018 21:15720
10/31/2018 21:302.854 10/31/2018 21:30721
10/31/2018 21:452.854 10/31/2018 21:45722
10/31/2018 22:002.888 10/31/2018 22:00725
10/31/2018 22:152.888 10/31/2018 22:15720
10/31/2018 22:302.888 10/31/2018 22:30717
10/31/2018 22:452.888 10/31/2018 22:45713
10/31/2018 23:002.858 10/31/2018 23:00708
10/31/2018 23:152.858 10/31/2018 23:15702
10/31/2018 23:302.858 10/31/2018 23:30695
10/31/2018 23:452.858 10/31/2018 23:45692
11/1/2018 0:002.779 11/1/2018 0:00690

Outcomes