Allow writing arrays as a time series to an output
I would like to be able to configure outputs in an analysis to write at multiple time points (which are defined by the result of an array function).
My use case is to:
- Configure an attribute as a Time Series Table Lookup
- Create an analysis that retrieves the values of this attribute as an array, e.g. using RecordedValues
- Transform the data using MapData
- Write the result back to another attribute that is configured as a PI Point
Can you clarify if your use case has 1 output PI Point or multiple PI Point(s)?
Is there any reason why you are not using RDBMS interface to bring your table data into the PI System? That would remove a lot of complexity and greatly improve performance.
Hi, I have a similar requirement. We are receiving Forecasted (Solar/Wind) data through UFL. Our Solar park for example, might only be 50% online (due to maintenance or other issues) and I would like to adjust the Future data by 50% in this example. I can reach up to the point to push the data into an array, include this factor in an array, but pushing the data back to a new (different) Future Data Tag does not seem to be an option currently.
I want to create the attached graph in PI Vision. The red and blue lines are coming from Pi Tags. The green line is a calculated line with the logic as given below.
1) get the reference date from "COM3 NPL DATE" PI Tag
2) if the reference date is null then and
if today is monday then
set the reference date as 3 days prior to Today's date
else if today is saturday then
set the reference date as 6 days prior to Today's date
set the reference date as Yesterday's date
3) get the points from "COMPUTER NET POWER FOR LOAD" PI Tag into a New PI Tag called "COM3 NET POWER FOR LOAD"
For step 1 & 2, I can get the value in the Reference Date variable
For step 3, I can use the following InterpolatedValues('SensorX','ReferenceDate -1','ReferenceDate','+1m') function. But I want to store the values of this function back to an output attribute and to a Pi Tag which I can use it in PI Vision along with other tags.