AI EV Charging Load Management
Controls charging schedules in real time to reduce peaks, avoid transformer overloads, and minimize charging costs.
The Problem
“Prevent EV charging peaks and grid overload”
Organizations face these key challenges:
Coincident charging creates sharp peaks that exceed transformer/feeder capacity and violate voltage limits, increasing outage risk and accelerating asset aging
Demand charges and real-time energy price volatility make unmanaged charging materially more expensive for depots, workplaces, and public sites
Limited real-time visibility and uncertainty in driver behavior (arrival/departure, required kWh) makes rule-based scheduling unreliable and leads to customer dissatisfaction
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.