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Existing utility software helps operators see what’s happening at individual substations and customer meters, but monitoring what happens in between is much more difficult. For a century, limited grid visibility worked just fine.
But as more EV chargers, home batteries, and rooftop solar systems come online, the transformers – critical “voltage managers” of your grid – can become strained and even damaged.
Without being able to quickly identify your most consistently stressed transformers, you’re stuck guessing which ones are most at risk. And with tens of thousands of distribution transformers for the average midsize utility, this can be like picking a needle out of a haystack.
Camus’ integrated platform enables you to ensure the long-term health of your equipment by instantly identifying highly-loaded transformers. Our software uses AMI data, GIS mapping, and third-party DER telemetry to accurately estimate loading on every distribution transformer.
Our machine learning-powered software provides an accurate view of the total loading through every single transformer by aggregating the measured and estimated net loads at every meter served.
Automatically identify your highest-loaded transformers and opportunities to avoid failures.
Evaluate potential impact of new DERs by reviewing loading over time.
Review voltage at downline meters to understand nearby grid conditions.
Put transformer locations in context with Maps, Streetview, and satellite overlays.
Understand how much time a transformer spends at high (or low) loading.
See median, minimum, and maximum voltages at downline meters.
Quickly view which downline meters are connected to each transformer.
See how each downline meter contributes a given transformer’s loading.
Export data via BigQuery for additional analysis in your team’s tool of choice.
