USE CASE
Transformer Health Monitoring
Grid continuously ingests data from AMI/MDM, ambient weather, and your asset registry to calculate transformer health signals, estimate loss-of-life, and drive closed-loop work orders in Grid Ops. The result: fewer failures, deferred capex, and safer, more reliable networks.
What Does Grid's Real-Time Transformer Health Monitoring Do?
Grid continuously computes loading and thermal KPIs so you can see, at a glance, which transformers are being pushed too hard.
Peak loading (% of nameplate)
See how “full” each transformer runs at its highest interval relative to rated kVA and flag peaks that threaten insulation life.
Time above nameplate (hours/day)
Track daily hours spent above 100% loading—one of the strongest drivers of thermal aging.
Load factor (%)
Compare average load to peak load to spot harsh thermal cycling that creates mechanical stress on windings and oil.
Voltage imbalance (%)
Identify sustained phase-to-phase voltage differences and trigger phase re-balancing or connection checks.
Additional Loss-of-Life (ALoL)
A proprietary IEEE- and IEC-informed model that estimates extra life consumed (in hours) versus nominal duty, based on interval-level thermal stress.
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How Does Grid’s Transformer Health Monitoring Work?
Grid’s architecture brings all relevant data into a single, unified model and closes the loop with operations:
Ingest & Unify
AMI/MDM intervals, feeder SCADA, asset registry, weather, and optional IoT sensors flow into Grid Vault via APIs, data streams, SFTP, and database connectors.
Model & score daily
Grid computes loading, thermal stress, power quality, and data quality signals, then applies a proprietary loss-of-life model informed by IEEE & IEC transformer insulation aging and thermal behavior.
Prioritize & Act
Transformers are ranked by ALoL and Health Index. Grid Ops converts these into work orders or recommendations (re-phasing, upsizing, balancing, cooling checks).
Verify & Learn
Post-maintenance, dashboards validate improvements; policies auto-tune based on observed results, without code changes.
Download The Datasheet
Advanced Sensor-Driven Analytics
Where transformer-level sensors are available (oil temperature, harmonics, etc.), Grid can extend monitoring with additional health checks:
Thermal cycles (count/day)
Track significant heating–cooling cycles that accelerate insulation and bushing wear and trigger smoothing or operational changes when cycles exceed targets.
Estimated hotspot / top-oil temperature (°C)
Model internal temperatures using load and ambient data; alert when hotspot temperatures exceed utility thresholds for sustained periods.
Total Harmonic Distortion (THD)
Monitor non-sinusoidal distortion that drives additional heating, losses, and potential protection trips; identify candidates for filtering or customer-side mitigation.
Download The Datasheet
Grid AI: The Future Of Transformer Health Monitoring
Agentic Intelligence for Transformer Assets
Daily autonomous checks
Run health reviews at a set time on ALoL, Health Index, time-above-nameplate, voltage/current imbalance.
Risk-based queues for every team
Auto-generate prioritized lists of transformers by risk and required action—separately for field crews, planners, and leadership.
Action automation & closed loop
Auto-create work orders with recommended remedies, including safety steps, parts lists, and due dates.
Self-tuning policies
Thresholds adapt to climate, seasonality, holidays, and changes in feeder topology; weightings and SLAs update as well.
Multi-agent workflows
Grid AI’s Query Agent delivers daily briefs, the Builder Agent spins up dashboards & reports, and the Ops Agent orchestrates BPMN-style workflows.
GridAI brings speed, accuracy, and autonomy to every utility team—from field ops to analytics.
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Why Do Utilities Choose Grid for Monitoring Transformer Health?
Fast Time‑to‑Value
Start with a data-only assessment and move to closed-loop workflows in weeks, not years.
Closed-loop from insight to field action
Move seamlessly from health index and ALoL to work orders, safety steps, and SLA tracking.
Deep integrations with your ecosystem
Connect HES, MDM, SCADA, CIS, GIS, ERP, and WFM via APIs, data streams, SFTP, or DB connectors.
Scalable, fleet-wide prioritization
Health Index and ALoL let you manage thousands of transformers as a portfolio, not one complaint at a time.
Super-fast Onboarding, Immediate Results
Step 1
Data-Only Assessment
Start with 60–90 days of AMI/MDM plus asset registry data. Grid scores your transformer fleet and surfaces the first set of high-risk units.
Step 2
Workshop & KPI Alignment
Run a joint workshop to align on KPIs—e.g., reduce time-above-nameplate by 50%, cut ALoL in the top decile by 30%, or shrink voltage complaints in target feeders.
Step 3
Config & Setup
Configure data connectors, health index policies, and Grid Ops workflows. Because the solution is built on Grid’s existing platform, deployment is fast and incremental.
Step 4
Admin & Ops Training
Train core admins and ops leads on health dashboards, work order queues, and AI-driven recommendations.
Step 5
Go-Live & Closed-Loop Actions
Enable closed-loop work orders (either in Grid Ops or your existing WFM) and start tracking quantified improvements to risk, failures, and spend.
Ready to see how Transformer Health Monitoring would work on your network?
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Robust Security and Compliance
Grid ensures your data is fully encrypted during storage and transmission. We are SOC 2 Type 2, ISO, and GDPR certified, adhering to the highest privacy and security standards.
