AI EV Charging Network Optimization
Optimizes charger siting, capacity planning, and utilization using demand forecasting, traffic patterns, and grid constraints.
The Problem
“Optimize EV charging to cut grid costs”
Organizations face these key challenges:
Demand charge spikes and transformer/feeder constraint violations from uncoordinated simultaneous charging
Low utilization at some sites and chronic congestion at others due to poor siting, pricing, and load forecasting
Operational complexity across tariffs, wholesale price volatility, DER/storage integration, and uptime requirements
Impact When Solved
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.
AI Grid Congestion Management
This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.