AI+能源，如何“+”出新未来？

Core Insights - The digital transformation of China's energy and power industry has progressed from "direction exploration" to "system practice" under the guidance of the "dual carbon" goals and the strong drive for a new power system [1] - Experts emphasize the need for collaboration among government, industry, academia, research, and application sectors to overcome challenges in data, algorithms, computing power, talent, standards, and more [1] Group 1: Digital Transformation and AI Integration - Digital technologies have deeply integrated into every aspect of the energy sector, transitioning from reliance on "human resources" to "data intelligence" [3] - Major energy companies like China Huadian and Three Gorges Group have established comprehensive digital systems covering the entire lifecycle from construction to intelligent operation and maintenance [3] - AI applications in the power grid have evolved from basic inspections to complex decision-making processes, enhancing reliability management and power prediction accuracy [4] Group 2: Challenges in AI and Data Utilization - The energy sector faces structural and foundational challenges in AI integration, particularly regarding data sharing mechanisms, standardization, and model reliability [6] - Data quality issues persist, with high-value data being scarce and costly to label, hindering the depth of AI applications [6][7] - The fragmented development of AI technologies leads to resource redundancy and barriers within the industry, limiting overall efficiency and sustainable growth [7] Group 3: Future Directions and Ecosystem Development - A systematic approach is needed to transition AI in the energy sector from "empowerment" to "enabling," focusing on innovation and ecosystem support [9] - The National Development and Reform Commission and the National Energy Administration aim to promote the deep application of over five professional large models and explore numerous empowering scenarios by 2027 [9] - Building an open and collaborative industrial ecosystem and standard system is essential for supporting technology implementation and promotion [9] Group 4: Talent Development and Policy Support - The energy sector requires a significant number of skilled professionals, with a projected talent gap exceeding 1 million in the renewable energy field [10] - Strategies such as industry-academia cooperation and establishing training bases are necessary to address the talent shortage [10] - Policies must be refined to encourage innovation and establish clear safety boundaries and ethical standards for AI applications in the energy sector [10]