by Xinhua Writer Liu Ziyan

BEIJING, July 20 (Xinhua) -- China's energy storage industry is in line to benefit first from a drive to promote greater integration of the country's artificial intelligence (AI) and new energy sectors as part of its development blueprint for the next five years.

The 15th Five-Year Plan period (2026-2030) highlights the two sectors as key drivers of growth.

"AI is a key enabler for energy storage companies to achieve technological leadership and maximize returns," said Lyu Zhe, vice president of Beijing HyperStrong Technology Co., Ltd., a leading Chinese energy storage company. "To maintain and enhance competitiveness, AI is very important."

From research and development (R&D) to operation and maintenance, AI enhances value across the entire energy storage industrial chain. On the R&D side, AI is fundamentally changing the traditional trial-and-error approach into a predictive one, shortening the development cycle of energy storage materials from years to months.

"Beyond battery materials, system integration technologies are also being upgraded," Lyu said. "AI can analyze operational data to identify areas for improvement. Testing and verification can also leverage AI to reduce costs and improve efficiency."

On the operation and maintenance side, AI's revenue-boosting effect is even more evident. One of its core values is reducing failures -- fewer unplanned outages mean longer operating hours and higher revenues.

Traditional safety monitoring approaches rely on threshold alarms, which often lag behind emerging problems. AI can identify hidden risk signals before battery thermal runaway through deep learning, enabling earlier warnings.

For instance, the TENER Smart Storage platform developed by Contemporary Amperex Technology Co., Ltd. (CATL) can issue fault warnings up to seven days in advance and help operation and maintenance personnel complete fault analysis within five minutes. HyperStrong's cloud platform can issue warnings three to 21 days in advance, with a fault-diagnosis accuracy of 99.7 percent, according to the company.

Another revenue-enhancing effect of AI lies in electricity trading. The core logic is to formulate charging and discharging strategies based on fluctuations in electricity prices. Large AI models take into account variables such as renewable energy output, weather conditions, grid congestion and market quotations to forecast electricity prices and formulate optimal strategies.

At Envision's smart energy storage station in Binzhou, in east China's Shandong Province, an AI trading agent has achieved 95 percent accuracy in predicting peak-valley electricity price spreads, according to the station. Trina Solar's system optimizes charging and discharging strategies every 15 minutes, improving energy conversion efficiency by 1.5 percent, according to the company.

NEW GROWTH POINT

A major opportunity AI brings to the energy storage sector is the coordination between computing power and electricity supply.

The year 2026 marks a critical turning point for such coordination, as it moves from conceptual consensus to practical implementation. China has issued a series of policy signals this year.

The Report on the Work of the Government released in March called for launching new infrastructure projects on hyper-scale intelligent computing clusters and coordinated development of computing capacity and electricity supply. The outline of the 15th Five-Year Plan calls for promoting the coordinated deployment of green electricity and computing power.

A plan for developing a new energy system during the 15th Five-Year Plan period further calls for ensuring a high-quality electricity supply for sectors including big data and AI.

AI computing centers have highly volatile loads and can experience sudden demand spikes, which conventional uninterruptible power supply systems may struggle to handle. Energy storage systems can serve as buffers. Meanwhile, computing centers can use energy storage facilities to capitalize on peak-valley electricity price differences and reduce electricity costs.

By 2030, electricity consumption by China's computing centers is expected to exceed 700 billion kilowatt-hours, accounting for more than 5 percent of the country's total electricity consumption, according to a China Galaxy Securities report cited by Xinhua. For energy storage companies, such estimates represent substantial opportunities.

Such coordination also offers new ways to consume green electricity, with a conceptual shift from "selling green electricity" to "selling tokens." GCL Energy Technology Co., Ltd. has said it will accelerate its transformation into a token trading service provider, offering full-stack services ranging from physical space and heterogeneous computing-power leasing to customized intelligent-computing solutions.

Behind the coordination between computing power and electricity supply lie not only commercial opportunities but also China's strategic considerations.

AI is a strategic technology driving a new round of scientific and technological revolution and industrial transformation. Therefore, if China successfully translates its strengths in the new energy sector into advantages in AI, it could greatly promote the integrated development of both fields.

"Only by combining the innovative strengths of China's domestically developed large AI models with the country's robust power supply capacity, particularly its abundant clean energy, can China turn its advantages in energy and electricity into competitive strengths in the AI industry," Ding Zhaohao, a professor at North China Electric Power University, said in an interview with China Central Television in March. ■