Why Meter-to-Transformer Connectivity Records Drift
The Problem
Outage response misses the right customers
When meters are recorded on the wrong transformer, the customers you believe are affected by an outage are not the ones who are.
Transformer overloads stay hidden
Overloads can hide behind meters recorded on other equipment.
DER and EV planning starts from bad data
Hosting capacity depends on knowing what is connected where. Wrong connectivity weakens every study built on it.
Crews search instead of fix
Confirming an assignment has traditionally meant sending someone to look. That works for a handful of meters, not a whole system.
Meter-to-Transformer Mapping Built Around Four Critical Capabilities
Designed for engineers who will check the work, built to turn AMI voltage data into a prioritized work list.
Findings That Hold Up
Results refresh every week, and a finding only reaches your work list once it has held up across repeated analyses. Two analytical methods with different strengths run in parallel, and the highest-priority findings are the ones both agree on.
- Weekly refresh as new data arrives
- Findings must recur before they are prioritized
- Two independent methods corroborate results
- Confidence measure and evidence on every finding, ready to load into your GIS
Uses the AMI Data You Already Collect
Utileyes needs only interval voltage, meter IDs, and meter locations from your AMI or meter data management system. Nothing is installed in the field, and the analysis covers your full meter population.
- No new hardware or field sensors
- 15-minute interval voltage preferred
- Several weeks of history to build each meter's voltage signature
- Your full meter population, not a sample
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Independent of Your GIS
Meters served by the same transformer see their voltage dip and recover together as load changes, even when they read at different voltage levels. Utileyes groups meters by that shared behavior, then compares the groups with your records, so it can catch errors your GIS has no way to see in itself.
- Meters grouped by how they actually behave electrically
- Grouping limited to meters close enough to share equipment
- Validates an existing mapping or builds one where none exists
- Likely transformer location estimated for unmapped groups
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Built Around Field Verification
Every finding is ranked and labeled with what the analysis could and could not establish, so crews go where they are most likely to find something. Where voltage alone cannot settle a question, the finding says so and leaves the call to field confirmation.
- Findings categorized as wrong feeder, unmapped meter, same-feeder conflict, missing from GIS, or location discrepancy
- Crews record on-site results directly in the work list
- GIS corrections detected automatically at the next refresh
- Meters confirmed correct are retired from future lists
