en.Wedoany.com Reported - China's National Development and Reform Commission, along with three other government departments, recently issued the "Action Plan for Promoting the Two-Way Empowerment of Artificial Intelligence and Energy," aiming to strengthen the foundational support of energy for AI development and leverage AI's multiplicative effect on energy transition, fostering mutual empowerment. As a key application scenario, the coal industry is accelerating its digital and intelligent transformation. At a recent conference held by the Informatization Branch of the China National Coal Association, participants exchanged views on the progress and challenges of "Coal + AI."

Wang Danshi, Deputy Director of the Informatization Branch of the China National Coal Association, stated that AI has become a core driver for the digital and intelligent transformation of coal enterprises, with large coal groups upgrading it from an auxiliary tool to a development strategy. China Energy Investment Corporation (CHN Energy) is deeply implementing its "AI+" special initiative, with relevant scenarios selected for the first batch of strategic high-value AI scenario libraries by the State-owned Assets Supervision and Administration Commission. China Coal Energy Group, China Coal Technology & Engineering Group, and Huaibei Mining Group have released their "AI+" action plans. Xuzhou Mining Group has published seven major AI scenario demands, leveraging AI to solve development challenges. AI applications now cover over 200 specific scenarios in coal mine production, safety supervision, and equipment maintenance. In terms of industry-specific large models, Shandong Energy Group's Pangu Mining Large Model, China Coal Energy Group's Lingjing Model, and China Coal Technology & Engineering Group's Sunstone Large Model are transforming general AI capabilities into specialized expertise. Coal mine autonomous driving technology is maturing. Nan Hui, Deputy Manager of the Intelligent Equipment Center at CHN Energy's Beidian Shengli Energy Company, introduced that the company has achieved routine unmanned operation of 29 heavy-duty mining trucks (220-ton class) and one hydrogen-powered mining truck (110-ton class), as well as remote loading for two WK-35 electric shovels. Zhang Pengpeng, Deputy General Manager of Beijing Longruan Technology Co., Ltd., stated that its Longruan Spatiotemporal Large Model now possesses multimodal capabilities and has been deployed in seven core scenarios, including intelligent security and intelligent design. Qiao Wei, Deputy General Manager of the Transparent Geology Company under the Xi'an Research Institute of China Coal Technology & Engineering Group, noted that transparent geology technology integrates over 20 specialized algorithms, covering 11 application scenarios such as mine geology and tunneling. In the Huangling mining area, the intelligent mining transparent working face system has achieved seven consecutive passes of unmanned mining, reducing the geological model error from 50 cm to 15 cm, with transparent mining coal output exceeding 30 million tons. Fang Jie, Product Director of the Suchang Research Institute under Lunkun Wisdom, introduced that its proactive remote condition monitoring service has helped Shandong Energy Group's Luxi Mining Co., Ltd. extend equipment lifespan by 20% and reduce maintenance costs by 15%. Industry-level AI foundational platforms are accelerating deployment. Shanxi Jinyun Company has been approved to build a national AI application pilot base (in the coal sector of energy resources). The Ordos Industrial Internet Platform, supported by Huawei Cloud's Pangu Mining Large Model, has established an integrated AI operation system featuring "central training, edge inference, cloud-edge collaboration, learning while using, and continuous optimization." In talent development, China University of Mining and Technology has pioneered an interdisciplinary program in intelligent mining, China University of Mining and Technology (Beijing) has established an AI college, Xi'an University of Science and Technology has launched an embodied intelligence talent training program, and CHN Energy has organized an AI competition to cultivate digital and intelligent talent.

The conference also highlighted current challenges. Participants identified deep-seated contradictions in three areas of digital coal construction: the data resource foundation, overall digital operations management, and the industry's digital ecosystem. Zhang Jianzhong, Director of the Mine Data Standards Institute under the China Coal Research Institute, pointed out that general large models face a "knows generalities, not specifics" dilemma when entering specific industries due to a lack of specialized data. He suggested building a trusted data space based on identity authentication and usage control to achieve "data usable but invisible," thereby promoting the circulation of industry data elements. Liu Qiaoxi, Chairman of Huaxia Tianxin IoT Technology Co., Ltd., stated that the digital and intelligent construction of coal mines has entered a deep-water zone, with comprehensive control still confined to large screens. Subsystems are built independently with different protocols, forming "chimney clusters" of data and control, where data cannot be interconnected and commands are difficult to coordinate. Control is disjointed—the "brain" and "limbs" are uncoordinated, with comprehensive control platforms emphasizing monitoring over control, resulting in long control processes and high latency. AI decisions have not been deeply integrated with control systems, preventing the formation of an intelligent closed loop. Wang Danshi noted a lack of effective coordination mechanisms among coal enterprises, equipment manufacturers, solution providers, and research institutes, making it difficult for the industry chain to form a cohesive force. The question of "who invests" continues to constrain the industry's digital and intelligent transformation. For next steps, the conference proposed five major directions: strengthening industry guidance, unblocking data bottlenecks (including advancing data standard and governance systems, and promoting the selection and recommendation of high-quality datasets), breaking through implementation bottlenecks, reinforcing talent guarantees, and bridging technological gaps (supporting the construction of pilot bases, computing centers, and open-source communities). Chen Yangcai, Deputy Secretary-General of the China National Coal Association, stated that efforts will be made to advance the construction of AI pilot bases for the coal industry, talent cultivation, and the building of a cooperative ecosystem.

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