Solution · 02

Make charging a flexible grid resource.

V2GDemand responsePower tradingReinforcement learning

Overview

A coordination layer between grid and station. Reinforcement-learning policies participate in demand response and power trading and dispatch V2G resources within compliance limits, lifting overall returns while protecting the charging experience.

Best suited for

  • Regional operators
  • Virtual power plant participants
  • Campus microgrids

Technology

  • DGX Spark
  • Omniverse
  • OpenUSD

Core modules

01

V2G dispatch

Assess dischargeable capacity and generate safe bidirectional plans.

02

Demand response

Ingest grid signals and adjust site load automatically.

03

Power trading

Buy and sell strategies driven by price forecasts.

04

Reinforcement learning

Train policies in the digital twin, then deploy to real sites.

Book a demo for this solutionNext solution: Digital twin charging station

HQZN / AI charging operating system

Bring your own station data and see forecasting, dynamic pricing and the digital twin at work.

Book a platform demo