AI in Distributed Energy Resource Management (DERMS)
Using Artificial Intelligence to balance millions of charging EVs on the grid.
Load Growth
+30%
Peak Demand 2035
AI Mkt
$12B
Energy AI by 2028
Latency
<100ms
Grid Response
Executive Summary
As EVs add massive load to the grid, AI algorithms are essential for "Load Balancing"—predicting demand and throttling charging speeds to prevent blackouts.
Predictive Load Balancing
When everyone plugs in at 6 PM, the grid strains. AI models analyze weather, traffic, and historical usage to predict these spikes. They then communicate with smart chargers to subtly lower charge rates (e.g., 7kW to 5kW) across thousands of cars, smoothing the curve without impacting the user experience.
Local Energy Markets
Blockchain and AI are enabling peer-to-peer energy trading. A solar-equipped home could sell excess power directly to a neighbor's charging EV. These micro-transactions require a high-trust digital ledger and settlement layer. EV.NET is the logical namespace for this decentralized energy exchange.
Cybersecurity
A connected grid is a vulnerable grid. AI is also deployed for anomaly detection, identifying potential cyber-attacks on charging networks before they spread. Trust in the network (.NET) is the foundational currency of the new energy economy.
Own the Digital Infrastructure
As the market for AI matures, authoritative digital real estate becomes scarce. EV.NET is the category-defining asset for this sector.
Acquire Domain Asset