Power for AI

Posted on 2025-10-132025-10-13 by lechuck park

AI Data Center Power Infrastructure: 3 Key Transformations

Traditional Data Center Power Structure (Baseline)

Power Grid → Transformer → UPS → Server (220V AC)

Single power grid connection
Standard UPS backup (10-15 minutes)
AC power distribution
200-300W per server

3 Critical Changes for AI Data Centers

🔴 1. More Power (Massive Power Supply)

Key Changes:

Diversified power sources:
- SMR (Small Modular Reactor) – Stable baseload power
- Renewable energy integration
- Natural gas turbines
- Long-term backup generators + large fuel tanks

Why: AI chips (GPU/TPU) consume kW to tens of kW per server

Traditional server: 200-300W
AI server: 5-10 kW (25-50x increase)
Total data center power demand: Hundreds of MW scale

🔴 2. Stable Power (Power Quality & Conditioning)

Key Changes:

800V HVDC system – High-voltage DC transmission
ESS (Energy Storage System) – Large-scale battery storage
Peak Shaving – Peak load control and leveling
UPS + Battery/Flywheel – Instantaneous outage protection
Power conditioning equipment – Voltage/frequency stabilization

Why: AI workload characteristics

Instantaneous power surges (during inference/training startup)
High power density (30-100 kW per rack)
Power fluctuation sensitivity – Training interruption = days of work lost
24/7 uptime requirements

🔴 3. Server Power (High-Efficiency Direct DC Delivery)

Key Changes:

Direct-to-Chip DC power delivery
Rack-level battery systems (Lithium/Supercapacitor)
High-density power distribution

Why: Maximize efficiency

Eliminate AC→DC conversion losses (5-15% efficiency gain)
Direct chip-level power supply – Minimize conversion stages
Ultra-high rack density support (100+ kW/rack)
Even minor voltage fluctuations are critical – Chip-level stabilization needed

Key Differences Summary

Category	Traditional DC	AI Data Center
Power Scale	Few MW	Hundreds of MW
Rack Density	5-10 kW/rack	30-100+ kW/rack
Power Method	AC-centric	HVDC + Direct DC
Backup Power	UPS (10-15 min)	Multi-tier (Generator+ESS+UPS)
Power Stability	Standard	Extremely high reliability
Energy Sources	Single grid	Multiple sources (Nuclear+Renewable)

Summary

✅ AI data centers require 25-50x more power per server, demanding massive power infrastructure with diversified sources including SMRs and renewables

✅ Extreme workload stability needs drive multi-tier backup systems (ESS+UPS+Generator) and advanced power conditioning with 800V HVDC

✅ Direct-to-chip DC power delivery eliminates conversion losses, achieving 5-15% efficiency gains critical for 100+ kW/rack densities

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With Claude

800V HVDC

Posted on 2025-06-272025-06-27 by lechuck park

AI Data Center: Server-Side Power Management Transition from AC to DC

Traditional AC Server Power Management (Upper Section)

AC Power Distribution Chain

6.6kV to 380V AC: Primary voltage step-down transformation
UPS (Outage Fast Recovery): Backup power for short-term outages
Distribution Cutoff, Regulation: Power distribution control and voltage regulation
AC to DC for Server: Final AC-DC conversion at server level
Output: AC 380V (KW level)

New DC Server Power Management Technology (Lower Section)

DC Power Distribution Chain

AC to DC Conv 800V HVDC: Direct high-voltage DC conversion
ESS (Energy Storage System): Integrated energy storage solution
Digital Control: Advanced digital power management
DC to DC Down for Server: DC-DC step-down conversion for servers
Output: HVDC 800V (MW level)

Key Technology Advantages of DC Transition

Power Quality Enhancement

PF Up, Harmonics Dn: Improved power factor and reduced harmonic distortion

Advanced Backup Capability

Long time Backup Peak Shaving: Extended backup duration with intelligent peak load management

Operational Efficiency

Lower Loss, High Density, Easy Control: Reduced conversion losses, compact footprint, simplified control architecture

Scalable Power Delivery

High Power Usage Available: Enhanced power capacity to meet AI server demands

Server-Side Power Management Transformation

This diagram illustrates the technological shift in server-side power management from traditional AC distribution (KW-level) to advanced DC distribution (MW-level), specifically designed to address the high-power requirements and efficiency demands of AI data centers. The DC approach eliminates multiple AC-DC conversion stages, resulting in improved efficiency and better power management capabilities.

With Claude

AI DC Energy Optimization

Posted on 2025-06-112025-06-10 by lechuck park

Core Technologies for AI DC Power Optimization

This diagram systematically illustrates the core technologies for AI datacenter power optimization, showing power consumption breakdown by category and energy savings potential of emerging technologies.

Power Consumption Distribution:

Network: 5% – Data transmission and communication infrastructure
Computing: 50-60% – GPUs and server processing units (highest consumption sector)
Power: 10-15% – UPS, power conversion and distribution systems
Cooling: 20-30% – Server and equipment temperature management systems

Energy Savings by Rising Technologies:

Silicon Photonics: 1.5-2.5% – Optical communication technology improving network power efficiency
Energy-Efficient GPUs & Workload Optimization: 12-18% (5-7%) – AI computation optimization
High-Voltage DC (HVDC): 2-2.5% (1-3%) – Smart management, high-efficiency UPS, modular, renewable energy integration
Liquid Cooling & Advanced Air Cooling: 4-12% – Cooling system efficiency improvements

This framework presents an integrated approach to maximizing power efficiency in AI datacenters, addressing all major power consumption areas through targeted technological solutions.

With Claude