GridPulse FDD
Detects and diagnoses distribution network faults while improving circuit balancing and DER-aware grid management through visibility into changing load patterns and intermittent distributed energy resources.
The Problem
“DER-aware circuit balancing and fault detection for distribution grids”
Organizations face these key challenges:
Limited real-time visibility into changing load patterns at feeder and phase level
Intermittent DER output creates uncertainty in net load and voltage conditions
Operational data is siloed across SCADA, AMI, OMS, GIS, and DERMS platforms
Static threshold alarms generate noise and miss emerging issues
Impact When Solved
The Shift
Human Does
- •Review SCADA alarms, outage reports, and periodic load studies to identify feeder issues
- •Manually compare AMI, GIS, OMS, and DER information to assess phase imbalance and loading risk
- •Estimate DER impacts and net load conditions using static assumptions and spreadsheet analysis
- •Plan switching, balancing, and restoration actions based on engineering judgment and existing procedures
Automation
- •Generate basic threshold alarms from operational monitoring systems
- •Surface historical trends and static reports for operator review
- •Flag obvious limit violations based on predefined rules
Human Does
- •Approve recommended balancing, switching, and DER-aware operating actions
- •Review prioritized fault diagnoses and decide response actions for high-risk conditions
- •Handle exceptions, conflicting field conditions, and safety-critical operating constraints
AI Handles
- •Continuously monitor feeder, phase, and DER behavior to detect emerging anomalies earlier
- •Forecast load, imbalance, and net load volatility under changing demand and intermittent DER output
- •Diagnose likely fault causes and prioritize circuits by overload, imbalance, and reliability risk
- •Generate and rank feasible balancing and reconfiguration actions to reduce stress and maintain reliability
Operating Intelligence
How GridPulse FDD runs once it is live
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not carry out balancing, switching, or DER-aware operating actions without approval from a distribution operator or control room supervisor [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in GridPulse FDD implementations:
Key Players
Companies actively working on GridPulse FDD solutions: