As China’s renewable energy capacity soars, the nation is embracing artificial intelligence (AI) to revolutionize energy storage systems (ESS), propelling it towards its ambitious “carbon peak” and “carbon neutrality” goals.
By the end of May, China’s total installed power generation capacity reached a staggering 3.61 billion kilowatts (kW), marking an impressive 18.8% year-on-year increase, according to the National Energy Administration (NEA). Photovoltaic (PV) power generation led the charge, adding nearly 200 million kW of new grid-connected capacity from January to May—a 57% surge compared to the previous year. This milestone pushed China’s cumulative installed PV capacity past the 1 billion kW threshold, equating to the power of approximately 48 Three Gorges Dams.
However, the rapid expansion of renewable energy highlights the pressing need for advanced energy storage solutions. The intermittent and variable nature of solar and wind power demands robust ESS technologies to integrate renewables into the grid seamlessly and maintain a stable power supply. These technologies include pumped hydro storage, battery storage, thermal storage, and mechanical storage, each offering unique benefits.
“The significance of energy storage in transforming the power system is revolutionary,” said Liu Yafang, former deputy director-general of the NEA and now a part-time professor at Zhejiang University.
Despite the growth, China’s energy storage capacity remains insufficient to match its burgeoning renewable energy sources. “Under the traditional power model, electricity had to be generated and consumed instantly. The large-scale development and grid integration of new energy sources bring rapid growth but also challenges in absorption and stability,” Liu explained.
The Chinese government recognizes the strategic importance of new-type energy storage. In the 2024 Government Work Report, energy storage was highlighted as a “new quality productive force,” underscoring its role in building a modern power system aligned with the nation’s carbon goals.
Boosting demand further, a notice from the National Development and Reform Commission (NDRC) and the NEA announced that starting June 1, all new energy power generation connected to the grid will enter the electricity market, with tariffs determined by market-based transactions.
“New energy cannot enter the market without energy storage,” Liu emphasized. “It’s impossible to generate revenue without energy storage.”
As demand for ESS grows, the role of energy management systems (EMS) becomes increasingly vital for the safe and efficient operation of energy storage facilities. “Effective safety management beyond the battery cells themselves is crucial,” stated Shi Zinan, director of the Smart Microgrid Institute at Tsinghua Sichuan Energy Internet Research Institute.
Industrial analyses reveal that failures in Battery Management Systems (BMS) and Thermal Management Systems (TMS) are primary safety hazards in energy storage power stations. “If these early hidden dangers persist, they will significantly accelerate battery degradation and greatly increase the risk of thermal runaway,” Shi warned.
AI is now pushing the boundaries of safety control in energy storage. Chinese companies have developed BMS systems that integrate data anomaly pattern recognition with deep reasoning techniques from large AI models, enabling intelligent fault diagnosis and smart operation strategies.
“AI-driven energy storage systems can ensure safety and intelligent operation,” Shi explained. “AI also empowers energy storage transactions, enhances economic benefits, and assists in grid efficiency regulation.”
Liu echoed this sentiment, stating, “The emergence of new technologies, especially the vigorous development of AI technology in China, will undoubtedly promote the application, deployment, and high-quality development of energy storage, optimizing operational strategies.”
The ultimate value of new-type energy storage lies in its potential to drive the transformation of the energy system—from a fossil-fuel-dependent, centralized supply model to one dominated by renewable energy with both distributed and centralized collaboration.
