Utilities & Infrastructure

Vantage connects to SCADA systems, asset management databases, and customer information systems to give utility operators real-time visibility into grid health, water distribution, and infrastructure condition. Build predictive maintenance programs, automate regulatory reporting, and respond to outages faster with AI-powered analysis.

Predict Grid Asset Failures Before They Cause Outages

Score transformer and switchgear health using sensor data and predict failures before they happen.

Scenario: An electric utility managing 5,000+ distribution transformers needs to prioritize capital replacement and maintenance using condition-based health scoring rather than age-based replacement.

Workflow Steps:

1. Schedule Trigger — Run every 30 minutes
2. Database Query (PostgreSQL) — Pull transformer telemetry from SCADA: oil temperature, winding temperature, dissolved gas analysis (DGA) results (hydrogen, methane, ethylene, acetylene), load factor, tap changer operations count
3. Database Query (MSSQL) — Pull asset master data from the EAM: asset ID, manufacturer, install date, age, kVA rating, last maintenance date, location, serving customers count
4. Join — Merge real-time telemetry with asset attributes
5. Computed Column — Calculate health indicators:
   • DGA risk index: weighted combination of gas ratios (Doernenburg, Rogers ratios)
   • Thermal risk: peak temperature / rated temperature × loading factor
   • Age factor: remaining useful life percentage based on IEEE C57 aging equations
   • Operations stress: tap changer operations vs. maintenance interval
6. AI Enrichment — Generate composite health score (0–100) for each transformer:
   • HEALTHY (80–100): routine monitoring
   • WATCH (60–79): increase inspection frequency
   • CRITICAL (< 60): schedule immediate assessment
   • Include failure mode prediction: thermal degradation, dielectric breakdown, mechanical failure
7. Multi-Conditional — Route by health classification:
   • CRITICAL → Create Issue (Jira) for emergency maintenance crew + Send Email to reliability engineering manager with diagnostics summary + Dashboard Output (Event Monitor Tile)
   • WATCH → Dashboard Output (List Tile — watchlist queue) + DB Write (update next-inspection date to 30 days)
   • HEALTHY → Dashboard Output (Metric Tile — fleet health score)
8. Geocode — Resolve substation coordinates for mapping
9. Dashboard Output — Populate:
   • Map Tile — Substations color-coded by worst-case transformer health
   • Line Tile — Temperature and DGA gas trends by transformer
   • Forecast Tile — Projected failure probability over 6/12/24 months
   • Histogram Tile — Age distribution of transformer fleet
   • Metric Tile — Fleet average health score, critical asset count, replacement backlog size
   • Table Tile — Asset inventory with health score, age, and recommended action
   • Scatter Tile — Health score vs. customer count served (prioritize high-impact assets)
10. Write PDF — Generate quarterly asset condition report for the public utility commission

Key Nodes: Schedule Trigger, Database Query (PostgreSQL, MSSQL), Join, Computed Column, AI Enrichment, Multi-Conditional, Geocode, Create Issue (Jira), DB Write, Write PDF, Send Email, Dashboard Output

Manage Outages and Track Restoration in Real Time

Track outage events, coordinate crew dispatch, and monitor restoration progress in real time.

Scenario: During a severe weather event, a utility's distribution system experiences dozens of simultaneous outages. The storm center needs real-time visibility into affected customers, crew status, and estimated restoration times.

Workflow Steps:

1. Logical Trigger — Fire when an outage event is logged in the OMS (Outage Management System)
2. Database Query (PostgreSQL) — Retrieve outage details: feeder, circuit, device, cause code, estimated customers affected, timestamp
3. Database Query (MSSQL) — Pull crew dispatch status: crew ID, current assignment, estimated arrival, equipment on truck
4. Geo Filter — Identify all customers within the affected service area using the circuit/feeder topology
5. Aggregation — Calculate outage impact:
   • Total customers out
   • Critical facilities affected (hospitals, fire stations, water treatment plants)
   • Estimated restoration time based on cause code and crew distance
6. Multi-Conditional — Route by severity:
   • Critical facility affected → Send Email to emergency management coordinator + Send Message (Slack #storm-center) + Dashboard Output (Event Monitor Tile — priority)
   • > 1,000 customers → Send Message (Slack #storm-center) + Dashboard Output
   • < 1,000 customers → Dashboard Output only
7. Dashboard Output — Populate:
   • Map Tile — Outage area overlaid with crew locations and customer density
   • Event Monitor Tile — Active outage events with status and ETR
   • Timeline Tile — Crew dispatch → arrival → restoration sequence for each event
   • Metric Tile — Total customers out, crews deployed, SAIDI/SAIFI metrics
   • Bar Tile — Outages by cause code (equipment failure, weather, animal, vegetation)
   • Stat Tile — Average restoration time, longest active outage
8. Write CSV — Export outage data for post-event analysis and regulatory reporting (SAIDI, SAIFI, CAIDI calculations)

Key Nodes: Logical Trigger, Database Query (PostgreSQL, MSSQL), Geo Filter, Aggregation, Multi-Conditional, Write CSV, Send Email, Send Message, Dashboard Output

Monitor Water Quality and Distribution Pressure Continuously

Monitor water quality parameters and pressure across the distribution system to detect anomalies.

Scenario: A water utility needs continuous monitoring of chlorine residual, turbidity, pH, and pressure across 200 monitoring points to ensure compliance with EPA Safe Drinking Water Act requirements.

Workflow Steps:

1. Schedule Trigger — Run every 15 minutes
2. Database Query (PostgreSQL) — Pull real-time water quality data: monitoring point ID, chlorine residual (mg/L), turbidity (NTU), pH, temperature, pressure (psi), flow rate (GPM)
3. Aggregation — Calculate rolling averages and statistics per monitoring zone
4. Data Validation — Check regulatory compliance thresholds:
   • Chlorine residual: minimum 0.2 mg/L (EPA requirement)
   • Turbidity: < 1.0 NTU (treatment technique requirement)
   • pH: 6.5 – 8.5 range
   • Pressure: minimum 20 psi at all customer connections
5. Filter — Flag monitoring points outside compliance thresholds or trending toward exceedance
6. AI Enrichment — Classify anomalies: "Monitoring point WQ-142 shows chlorine residual dropping from 0.8 to 0.25 mg/L over the last 6 hours. Rate of decline suggests a potential main break or cross-connection in the zone. Recommend field investigation within 2 hours."
7. Multi-Conditional — Route by severity:
   • Below regulatory minimum → Send Email to water quality supervisor + Send Message (Slack #ops) + Create Issue (Jira) for immediate field investigation + Dashboard Output (Event Monitor Tile)
   • Trending toward exceedance → Send Message (Slack) to water quality analyst + Dashboard Output (warning)
8. Dashboard Output — Populate:
   • Map Tile — Monitoring points color-coded by compliance status
   • Line Tile — Water quality parameter trends with regulatory threshold lines
   • Event Monitor Tile — Active exceedance alerts
   • Metric Tile — Compliance rate %, average chlorine residual, system pressure
   • Stat Tile — Consecutive days in compliance (TCR compliance tracking)
9. Write PDF — Generate monthly Consumer Confidence Report (CCR) data for distribution to customers

Key Nodes: Schedule Trigger, Database Query, Aggregation, Data Validation, Filter, AI Enrichment, Multi-Conditional, Create Issue (Jira), Write PDF, Send Email, Send Message, Dashboard Output

Forecast Energy Demand and Balance Load Across the Grid

Forecast electricity demand, optimize generation dispatch, and monitor grid stability.

Scenario: A utility needs to forecast hourly load for the next 7 days to plan generation dispatch, manage peak demand charges, and comply with reliability standards.

Workflow Steps:

1. Schedule Trigger — Run every hour
2. Database Query (PostgreSQL) — Pull historical load data: hourly system load for the past 3 years
3. Database Query (MSSQL) — Pull current generation status: unit, fuel type, capacity, current output, heat rate, ramp rate
4. Web Scraper — Pull 7-day weather forecast: temperature, humidity, wind speed, cloud cover (weather is the strongest driver of electric load)
5. AI Enrichment — Generate hourly load forecast for the next 168 hours using:
   • Temperature–load regression (heating and cooling degree days)
   • Day-of-week and holiday patterns
   • Economic activity indicators
   • Solar generation forecast (cloud cover impact on distributed solar)
6. Computed Column — Calculate:
   • Peak demand for each day
   • Reserve margin: (available_capacity - peak_forecast) / peak_forecast * 100
   • Projected generation cost by dispatching units in merit order
7. Filter — Periods where reserve margin < 15% (reliability concern)
8. Multi-Conditional — Route by reserve margin:
   • < 10% (critical) → Send Email to grid operator + Send Message (Slack #dispatch) + Dashboard Output (Event Monitor Tile)
   • 10–15% (tight) → Send Message (Slack) to system planning + Dashboard Output
9. Dashboard Output — Populate:
   • Forecast Tile — 7-day hourly load forecast with confidence bands
   • Line Tile — Actual vs. forecasted load (real-time tracking)
   • Comparison Tile — Today's load shape vs. same day last year
   • Metric Tile — Current load, peak forecast, reserve margin %
   • Scenario Planner Tile — "What if temperature is 5°F higher than forecasted?" impact on peak demand
   • Bar Tile — Generation mix by fuel type (gas, coal, nuclear, wind, solar)

Key Nodes: Schedule Trigger, Database Query (PostgreSQL, MSSQL), Web Scraper, AI Enrichment, Computed Column, Filter, Multi-Conditional, Send Email, Send Message, Dashboard Output

Example Dashboard: Grid & Utility Operations Center

Build this dashboard to give control room operators and reliability engineers an at-a-glance view of system health, outages, and asset condition.

Row 1 — System Status

Row 2 — Geographic Overview

Row 3 — Asset Health & Outages

Row 4 — Water Quality & Load

Row 5 — Performance & Reliability

Row 6 — Maintenance & Compliance

Getting Started

To build utility operations workflows:

1. Connect your SCADA and asset systems — Add your SCADA historian, EAM, CIS, and OMS databases under Integrations
2. Start with asset health — Build a transformer health scoring workflow using DGA data and asset age
3. Add outage monitoring — Use Logical Trigger + Geo Filter + Map Tile for real-time outage visualization
4. Automate regulatory reporting — Schedule Write PDF for monthly quality reports and annual asset condition assessments
5. Build control room dashboards — Map, Metric, and Event Monitor tiles provide at-a-glance grid visibility