AI Driven Protection Coordination at Scale: How PPL Assessed 1,400 Feeders in Under Eight Hours

PPL Pennsylvania's protection engineering team manages coordination across 80,000+ protective devices — spanning reclosers, circuit breakers, and fuses — across a continuously evolving distribution grid. Grid growth and constant asset changes drive an ever-increasing demand for coordination validation, yet the traditional process remains manual and slow, leaving the system exposed to miscoordination that can cascade into outages affecting thousands of customers and costing millions of dollars. For the first time in PPL Pennsylvania's history, every feeder in the system has now been assessed for protection coordination — 1,400 feeders reviewed in under eight hours, a task that would otherwise require 10,000+ engineering hours.

This outcome was made possible by an AI and cloud-based solution that validates entire feeder coordination in seconds instead of hours. Two technical enablers underpin the approach at scale: a robust mathematical reconstruction of Time-Current Characteristic (TCC) curves defining how each device responds to fault conditions, and high-fidelity GIS data — including meticulous cable sizing and connectivity models — supporting accurate short-circuit calculations system-wide. Together, these enable automated, system-wide protection analysis that was previously impractical.

The business case was grounded in risk reduction and operational efficiency. Reducing validation time from hours to seconds minimizes grid exposure to miscoordination events and eliminates the manual review errors that can go undetected under traditional workflows. Accelerated protection refresh cycles reduce outage frequency, improve reliability performance, and lower crew costs associated with outage isolation and restoration.

To date, the solution has enabled rapid identification of protection miscoordination across more than 10,000 devices — a level of engineering review never previously achieved at this scale. This session will share the technical architecture, implementation challenges, and lessons learned throughout the development and deployment path.