WattShed Baseline
Check what the event actually curtailed, before paying on it.
Export your interval meter data to CSV, choose it here, and map the timestamp and kWh columns. Then describe the event: the date it ran, and the hours. This tool builds a comparable-day baseline for that window and reports what was actually curtailed against it, computed in this browser from your own export. Nothing is uploaded.
This replicates the comparable-day baseline convention published in ISO and utility demand-response manuals: the average of the event day's most comparable non-event days, matched by day type. It is cited here as a convention, not any ISO's certified settlement calculation, and it is not tied to a live program's official measurement and verification. Use it as an independent check before paying on a vendor-reported curtailment number, not as the number itself.
A baseline is only as good as the days behind it. Thin history, a hot or cold swing relative to the comparable days, or an occupancy change around the event date can all move the baseline as much as curtailment did. Read the signals below before trusting the headline figure, and treat this as a first read, not a verdict.
1. Load interval data
Choose a CSV file
Export interval meter data to CSV, then choose it here. Or load a small example first to see how the check works.
Computed entirely in this browser. Your interval data never leaves this device, and nothing is uploaded or stored.
Load interval data and describe the event to see a baseline here.
No file handy? Load the example data to see the full report first.
Related tools
How the baseline works
A convention borrowed from ISO and utility demand-response manuals.
Comparable days
The baseline for an event window is the average of the event day's 5 most comparable non-event days in your own interval history, not the same calendar date a year ago and not a single "typical" day picked by eye.
Day-type matching
Comparable days are matched by day type before they are averaged, so a weekday event is never baselined against weekend load, or the reverse. A day that ran an event itself is never used as another event's comparable day.
What weakens it
Thin history behind the event date, a weather swing between the comparable days and the event day, and an occupancy change around the event all move the baseline as much as curtailment did. None of that is visible from a column of interval readings alone.
Not a settlement calculation
This replicates the comparable-day baseline convention published in ISO and utility demand-response manuals, cited here as a convention. It is not any ISO's certified settlement calculation and is not tied to a live program's official measurement and verification.
Nothing beyond the columns you map is read for this report. Interval exports can carry an account number or a service address in an unrelated column; that column loads into this browser tab like the rest of the file and is never sent anywhere, but you are still handling that data, so treat the file the way your program already requires.