专家解读丨“人工智能+”能源战略迈向纵深期 煤炭行业把握创新应用脉搏

Core Viewpoint - The article emphasizes the importance of integrating artificial intelligence with the coal industry to drive high-quality development and transformation towards a smart, green economy, as outlined in the recent implementation opinions from the National Development and Reform Commission and the National Energy Administration [2][18]. Group 1: Opportunities for Coal Industry Transformation - The coal industry must embrace high-end, intelligent, and green development to ensure energy security during the ongoing green low-carbon transition in China [3]. - The implementation opinions highlight the need to cultivate and expand the intelligent industry, positioning the coal sector as a key testing ground for AI's integration into the real economy [4]. - The coal industry possesses vast amounts of untapped data, presenting a strategic opportunity for transformation through AI, particularly between 2025 and 2035 [5]. Group 2: Addressing Safety and Efficiency - The implementation opinions call for improvements in efficiency and safety in coal mining and surface production, especially in high-risk areas where over 65% of coal production occurs [6]. - AI technologies can shift the focus from passive responses to proactive safety measures, enhancing both national security and worker safety in coal mines [6]. Group 3: Evolving Development Models - The coal industry's development is shifting from a linear model based on resource reserves and capital investment to an exponential model driven by data generation and algorithm iteration [7]. - Future coal production will likely see a reduction in human labor, with a focus on data management and knowledge accumulation, marking a transition from resource operators to data operators [7]. Group 4: Technological Application and Integration - The current phase of coal mine intelligent construction is moving towards comprehensive technological upgrades, transitioning from algorithm assistance to a collaborative model involving specialized AI and multiple technologies [8]. - The implementation opinions advocate for the integration of intelligent models to achieve autonomous decision-making and control in production processes [10]. Group 5: Cross-Industry Collaboration - The coal industry is encouraged to develop new business models that integrate coal mining with electricity and chemical industries, fostering a collaborative development approach [11]. Group 6: Overcoming Challenges in AI Integration - Establishing a unified data standard and perception system is crucial to address the challenges of data sharing within the coal industry [13]. - The implementation opinions stress the need for reliable intelligent equipment and the integration of algorithms into core mining machinery to enhance operational efficiency [12]. Group 7: Long-Term Development Mechanisms - The coal industry's intelligent transformation requires a collaborative innovation ecosystem that combines data, technology, and application [14]. - There is a strong emphasis on cultivating interdisciplinary talent that combines mining expertise with AI knowledge to support the industry's transformation [15]. - The establishment of safety and ethical standards is essential to ensure the responsible application of AI in coal mining [16][17].