AI Smart Inverter Control

The Problem

“Grid instability from unmanaged inverter-based resources”

Organizations face these key challenges:

Fast voltage and thermal constraint violations driven by rapid PV ramps, EV charging clusters, and feeder reconfiguration

Static inverter settings that are safe but overly conservative, leading to unnecessary curtailment and poor hosting capacity utilization

Limited real-time visibility and coordination across diverse inverter fleets (different OEMs, firmware, and communications latency)

Impact When Solved

Maintain ANSI voltage compliance with 60–90% fewer violation minutes on targeted feedersIncrease DER hosting capacity 10–30% by dynamically managing voltage and congestionDefer feeder upgrades 1–3 years and reduce operational interventions 15–30%

The Shift

Real-World Use Cases

AI in Energy Industry: Smart Grid Optimization and Energy Management

This is like giving the entire power system—power plants, grids, and large customers—a real‑time ‘autopilot’ that constantly predicts demand, reroutes electricity, and tunes equipment so you use less fuel, waste less energy, and keep the lights on more reliably.

Time-SeriesEmerging Standard

8.5

AI Grid Congestion Management

This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.

optimizationgrowing

8.0