AI drives energy storage industry change

Energy storage provides a new green engine for data centers, and AI is also driving a new round of changes in the energy storage industry. There are two core points in the demand for energy storage technology in AI data centers: one is large-capacity storage; the other is safety. Energy storage companies are working towards these two directions.

 

Long-term energy storage (energy storage technology for more than 4 hours) has received widespread attention in recent years, triggering a wave of research and investment. Recently, Anhui China Power Xinlong Technology Co., Ltd. responded to investors and stated that the company's new energy technology team is currently carrying out long-term energy storage technology research and development and related product research and development.

 

"Due to its intermittent characteristics, wind and solar power generation cannot always provide stable electricity, so long-term energy storage technology has become particularly important." Feng Siyao told reporters that long-term energy storage technology can not only ensure the stability of power supply in data centers, but also promote the consumption of green electricity and support the sustainable development of the AI ​​industry.

 

 

In addition, driven by the AI ​​revolution, energy storage systems are undergoing a full-scale innovation from technical architecture to operation mode. It is understood that as one of the earliest companies to invest in the energy storage field, Beijing Haibosichuang Technology Co., Ltd. took the lead in deploying the digital empowerment of the entire life cycle of energy storage systems and is one of the first manufacturers to apply AI and big data to the energy storage field.

 

"Through intelligent management, energy storage systems can achieve accurate power dispatching and monitoring, improve operating efficiency and reduce energy consumption." Feng Siyao said.

 

Although the transformation of the energy storage field is constantly advancing, the construction and operation costs of energy storage systems are still high, especially in the case of large-scale deployment. The procurement, installation and subsequent operation and maintenance costs of energy storage equipment itself may become the main bottleneck of computing power storage projects.

 

"The computing power demand of the AI ​​industry continues to grow. How to reduce the construction cost of energy storage systems while ensuring power supply is the main issue that needs to be considered at present." Feng Siyao said that the current energy storage system construction still faces certain technical bottlenecks. For computing power-intensive applications, existing energy storage technologies may not be able to fully meet the needs of high intensity and high frequency. Therefore, it is particularly important to continue to tackle the development and application of large-scale long-term energy storage and high-efficiency energy storage systems.