AI technology key to green energy transition

The application of artificial intelligence technology will significantly improve energy utilization efficiency and accelerate the transition of traditional high-carbon industries towards green, low-carbon development, experts said during a forum focusing on carbon peak and carbon neutrality science and technology at the Zhongguancun Forum.

"AI technology is one of the key points in the innovation chain for the future energy structure. It plays a crucial role in promoting green energy transition and achieving carbon neutrality," said Ding Chibiao, vice-president of the Chinese Academy of Sciences, during the forum held in Beijing on Friday.

He added that this trend has boosted the efficiency of the chemical industry and promoted energy conservation and emission reduction, thereby contributing to China's dual carbon goals of peaking carbon emissions before 2030 and achieving carbon neutrality before 2060.

Ye Mao, a researcher at the Dalian Institute of Chemical Physics of the CAS and head of the intelligent chemical engineering large model team, mentioned that some chemical companies have pioneered the application of AI models, which has sparked industry interest in this technology.

The rapid development of current AI models has led to increased acceptance within the industry. According to a survey his team did, nearly 50 chemical companies have had their engineers and technicians try the intelligent chemical models, and this number is continually growing, he said.

Since 2016, the team led by Liu Zhongmin, director of the DICP and academician of the Chinese Academy of Engineering, has been dedicated to applying AI technology to chemical engineering development.

In March of last year, they launched the chemical engineering large model ChemELLM, which achieved autonomous design and optimization of chemical knowledge retrieval and process flows. In November, ChemELLM 2.0 was released.

"The upgraded version shows significant improvements in industrial catalysis, chemical foundations, and chemical safety," Ye said, adding that these advancements enable the intelligent chemical models to cover a broader range of chemical application scenarios.

"We have found during our interactions with companies that traditional engineers and AI model-based human-machine collaboration will coexist for a long time and that there will be a period of adjustment. Building an intelligent chemical ecosystem will take some time," he said.

"We hope to assist the chemical industry in its intelligent upgrading, enhance production efficiency and intrinsic safety, and further support the energy revolution, dual carbon goals, and new industrialization," Ye said.

In 2022, the CAS formulated and implemented the Strategic Action Plan for Science and Technology Supporting Carbon Peak and Carbon Neutrality.

"In the future, the CAS will further deepen collaborative innovation with all sectors of society through interdisciplinary and cross-field integration to collectively advance AI-assisted low-carbon energy development," Ding said.