AI Data Center Grid & Power Sizing Simulator
Model gigawatt-scale AI compute load, 24-hour supply dispatch, substation interconnect capacity, BESS storage, and clean firm power (SMR & Fusion).
Infrastructure & Generation Sizing
| IT Compute Direct Load | 120.0 MW |
| Thermal Overhead (PUE) | 21.6 MW |
| Grid Transmission Allocated | 120.0 MW |
| Firm Clean (SMR + Fusion) | 0.0 MW |
| Behind-The-Meter Renewables | 160.0 MW nameplate |
| BESS Max Stored Energy | 160 MWh |
Reliability & Grid Stress Analysis
| Substation Capacity Margin | -21.6 MW (Over) |
| Curtailed Surplus Energy | 148.2 MWh/day |
| BESS Daily Cycles | 0.85 cycles/day |
| Interconnect Queue Risk | Medium (3-5 yr lead) |
| Carbon Intensity Score | Grade B+ |
| Levelized Cluster Energy Spend | $0.079 / kWh |
Solving the AI Power Grid Bottleneck
Why hyperscalers, fusion startups, and utilities are converging on next-generation on-site clean power.
Substation Interconnection Queues
Traditional utility grid interconnects now face 4 to 7 year delays across PJM, ERCOT, and CAISO. High-density AI training clusters exceeding 100 MW require dedicated behind-the-meter generation or transmission upgrades before compute clusters can energize.
SMR Nuclear & Commercial Fusion
Unlike intermittent solar and wind, advanced nuclear fission (SMRs) and magnet-confined fusion provide continuous 24/7/365 firm power without costly gigawatt-hour battery banks, directly matching the continuous 95%+ baseload factor of foundational training models.
PUE & Liquid Cooling Density
As rack power densities surpass 100 kW to 150 kW per rack for next-gen GPU clusters, direct-to-chip liquid cooling and two-phase immersion bring PUE down from 1.45 to <1.15, eliminating dozens of megawatts of parasitic chiller load from the local substation.