With the rapid development of artificial intelligence (AI) technologies, global demand for high-performance computing is growing at an unprecedented pace. Applications such as large language models, AI agents, and intelligent analytics platforms require continuously running high-density GPU clusters, which drives the expansion of data center infrastructure. Alongside computing growth comes a significant demand for stable and reliable electricity supply.

Energy Challenges for AI Data Centers

AI data centers differ from traditional data centers in several key ways:

• High-power density equipment: GPU clusters and AI accelerators consume tens of kilowatts per rack during large model training.

• Continuous AI services: Real-time inference, automation, and AI agent services require 24/7 power supply.

• Cooling infrastructure: High-density computing generates substantial heat, requiring efficient cooling to maintain server stability.

These factors result in large and fluctuating power demand, challenging conventional power grids. During peak loads, electricity supply may be insufficient, and voltage fluctuations could impact GPU cluster operation.

The Role of Energy Storage Systems

To address these challenges, Battery Energy Storage Systems (BESS) are becoming an essential part of AI data center infrastructure. Core functions include:

• Peak shaving: Releasing stored energy during peak demand to reduce grid stress.

• Backup power: Providing stable electricity during grid outages or faults to ensure uninterrupted AI workloads.

• Renewable energy integration: Storing solar or wind power during off-peak periods and releasing it during high-load periods, optimizing energy efficiency.

Energy storage improves reliability while reducing operating costs for AI data centers.

Dagong ESS Products for AI Data Centers

Different data center scales require different types of energy storage solutions:

1. Medium-scale commercial energy storage

• 100kWh–144kWh Air-Cooled ESS

• 241kWh–418kWh Air-Cooled ESS
  Modular systems allow flexible expansion, suitable for medium and small AI data centers.

2. High-density liquid-cooled energy storage

• 241kWh Liquid-Cooled ESS

• 372kWh Liquid-Cooled ESS

  Liquid-cooling ensures stable temperature in high-power environments, enhancing efficiency and reliability.

3. Containerized large-scale energy storage

• 5MWh Liquid-Cooled ESS Container
  Suitable for campus-level or ultra-large data centers, with real-time monitoring and fault logging to ensure stable high-volume computing.

Dagong ESS systems offer high cycle life (8000+ cycles) and long-term reliability (over 15 years), supporting continuous AI infrastructure operation.

The Future of Energy Storage and AI

As AI applications expand, the number of AI data centers worldwide will continue to grow, driving new opportunities in the energy storage market. Future value of energy storage includes:

• Ensuring stable power supply for AI workloads

• Supporting grid flexibility and energy efficiency

• Integrating renewable energy to reduce carbon footprint

• Optimizing operational costs for data centers

In conclusion, the rapid growth of AI data centers is driving global energy storage demand, making storage systems a core technology for supporting AI computing infrastructure.