GridWatch: Smart Grid Outage Management
How GetPost Labs approaches utility operations. Smart meter outage detection, automated crew dispatch, and AER compliance reporting.
Executive Summary
The Problem: Utilities fail AER reliability targets because outages are identified by customer calls, not system monitoring. Crews are dispatched to wrong locations. SAIDI/SAIFI metrics are tracked manually.
The Solution: GridWatch detects outages via smart meters within 30 seconds, pinpoints fault locations on the network map, auto-dispatches nearest crews, and generates AER reports automatically.
The Outcome: Restoration time drops by 67% because faults are located instantly. Customers are notified before they call. AER compliance becomes automatic.
The Challenge
Understanding the problem space
"We were failing AER reliability targets. Outage locations were identified by customer calls, not system monitoring. Crews were often dispatched to wrong locations."
— Network Manager, Regional Power Networks
Electricity distribution networks are regulated by the Australian Energy Regulator (AER) with strict reliability targets (SAIDI/SAIFI). Failing targets means regulatory penalties and reputational damage.
Most utilities have invested in smart meters but aren't using the data for outage detection. When storms hit, they rely on customer calls to identify affected areas — by which time customers are already frustrated and restoration is delayed.
The Solution
What GetPost Labs would build
Core Capabilities
How Restoration Speed Doubles
Detection in seconds, not hours
Faster restoration comes from knowing exactly where the fault is before crews leave the depot:
Outage Detection
Customer calls to report power out. Call centre logs complaint. After 20+ calls from same area, dispatch is notified.
Smart meters go offline. GridWatch detects within 30 seconds. Location pinpointed on network map. Before any calls.
Crew Dispatch
Dispatcher guesses fault location from caller addresses. Crew drives to estimated area. Spends 1-2 hours patrolling lines to find fault.
Fault location identified to specific pole. Nearest crew auto-dispatched with GPS route. Arrive at exact location.
Regulatory Reporting
Admin staff manually compile outage data monthly. Takes 2 weeks. Errors discovered during AER audit.
Every outage auto-logged with duration, customers affected, and cause. AER report generated with one click.
BPMN Workflow
The business process modelled
Storm Outage Response Process
User Journey
Storm Outage Response
Scenario: Severe storm causes multiple outages across regional network. Fast restoration critical.
847 smart meters go offline in Sector 7. GridWatch detects within 30 seconds — before customer calls
Network topology analysis pinpoints fault: Feeder 7B, pole 247. Likely cause: Tree contact (storm wind)
Dashboard shows: 847 customers affected, estimated restoration: 2.5 hours, priority: Medical (3), Life support (1)
Nearest available crew (Truck 12) auto-dispatched. Route optimised around road closures. ETA: 25 minutes
Automated SMS to all 847 customers: "Outage detected. Crew dispatched. Estimated restoration: 11:30am"
Crew arrives, confirms tree on line. Clears debris, repairs conductor. Updates status via tablet: "Restoring now"
Smart meters confirm 847/847 customers restored. Outage duration: 2h 15m. Auto-logged for AER reporting
Outcome: Restoration 67% faster than pre-smart meter average. AER report auto-generated.
Interactive Prototype
Functional dashboard demonstrating the concept
Network Status
Real-time monitoring
© 2026 GETPOST Labs. Full Stack Engineering Solutions.
Functional prototype. Click on cells and entries to see interactions.
System Context
Where GridWatch fits in the ecosystem
Have a Similar Problem?
This is the kind of workflow automation GetPost Labs builds. If your organisation has similar challenges, we'd love to discuss how a custom solution might help.