With the rapid development of artificial intelligence technologies, AI data centers have become a critical part of global digital infrastructure. From large language model training to real-time AI inference services, these computing workloads require massive GPU clusters operating continuously, which leads to significant electricity demand.

In this context, reliable and stable electricity supply becomes essential for AI data center operations. Traditional power grids may struggle to provide consistent power during peak loads or grid fluctuations. As a result, many AI data centers are adopting Battery Energy Storage Systems (BESS) to improve energy stability and efficiency.

Power Stability Requirements for AI Data Centers

AI data centers require higher power stability compared with traditional IT infrastructure. GPU clusters performing large-scale model training depend on uninterrupted electricity supply. Even short power disruptions or voltage fluctuations may interrupt computing tasks or cause data loss.

The power demand of AI data centers mainly comes from several sources.

First, high-performance GPU servers. Large-scale AI training clusters may involve hundreds or thousands of GPUs running simultaneously, with each rack consuming tens of kilowatts.

Second, continuous AI inference services. Many AI applications operate 24/7, including intelligent assistants, automated analytics, and industrial AI systems.

Third, data center cooling systems. High-density computing hardware generates significant heat, requiring efficient air cooling or liquid cooling to maintain stable temperatures.

These factors make AI data centers highly energy-intensive facilities.

Key Roles of Energy Storage in AI Data Centers

Energy storage systems provide several advantages for AI data center energy management.

1. Power Stability and Backup Power

Energy storage systems can immediately supply electricity during grid fluctuations or outages, ensuring uninterrupted computing operations. Compared with diesel generators, battery storage systems respond much faster.

2. Peak Shaving

During peak electricity demand, energy storage systems can release stored power to reduce pressure on the grid and lower electricity costs.

3. Renewable Energy Integration

Many data centers are adopting renewable energy sources such as solar or wind power. Energy storage systems store excess electricity and release it when computing demand increases.

4. Improved Energy Flexibility

Energy storage allows data centers to manage electricity supply more efficiently and balance power loads.

Energy Storage Solutions for AI Data Centers

Different scales of data centers can adopt different energy storage solutions.

For medium-sized AI data centers or edge computing facilities, modular storage systems are suitable, including:

• 100kWh–144kWh Air-Cooled ESS

• 241kWh–418kWh Air-Cooled ESS

These modular systems allow flexible capacity expansion for commercial and industrial applications.

For high-density computing environments, liquid-cooled systems offer improved thermal management:

• 241kWh Liquid-Cooled ESS

• 372kWh Liquid-Cooled ESS

Liquid cooling improves system efficiency and battery lifespan.

For large AI computing campuses, containerized energy storage systems provide larger capacity:

• 5MWh Liquid-Cooled ESS Container

These systems support campus-level energy management and real-time monitoring.

Lifespan and Reliability of Energy Storage Systems

Modern energy storage systems commonly use lithium iron phosphate (LFP) batteries, known for safety and long lifecycle.

Typical performance includes:

• More than 8000 charge cycles

• Service life exceeding 15 years

Advanced Battery Management Systems (BMS) continuously monitor battery status to ensure safe and stable operation.

These technologies enable energy storage systems to reliably support long-term AI data center operations.

Energy Infrastructure for the AI Era

As AI technologies continue to develop, the number of AI data centers worldwide will keep growing. AI computing is expected to become a major contributor to global electricity demand.

In this context, energy storage systems will become an essential part of AI infrastructure by:

• ensuring stable power supply

• improving grid energy efficiency

• enabling renewable energy adoption

• reducing data center operating costs

Energy storage will play an increasingly important role in supporting global AI data center infrastructure.