算电协同发展

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两部门:到2027年推动五个以上专业大模型在电网、发电、煤炭、油气等行业深度应用-财经-金融界
Jin Rong Jie· 2025-09-08 02:38
Core Viewpoint - The implementation opinion aims to promote the integration of artificial intelligence (AI) and the energy sector, establishing a framework for high-quality development by 2027 and achieving world-leading levels by 2030 [1][10][12]. Group 1: Implementation Goals - By 2027, the initial framework for the integration of energy and AI will be established, focusing on the deep application of over five professional large models in various energy sectors such as power grids, generation, coal, and oil and gas [1][12]. - The plan includes identifying over ten replicable and competitive demonstration projects and exploring a hundred typical application scenarios [1][4][12]. - By 2030, the goal is to achieve systematic breakthroughs in AI-specific technologies and applications within the energy sector, enhancing safety, green transformation, and efficiency [5][13]. Group 2: Key Tasks - The implementation opinion outlines several key tasks, including empowering various energy scenarios with AI, focusing on coal, electricity, oil, and gas [6][7]. - It emphasizes the need for a comprehensive approach to AI applications across eight major scenarios, including smart grid, new energy, and nuclear power [7][8]. - A total of 37 key tasks have been identified, with specific applications in oil and gas, coal, electricity, and renewable energy [7][8]. Group 3: Technical Support - The opinion highlights the importance of strengthening the foundational technologies for AI applications in the energy sector, focusing on data, computing power, and algorithms [8][32]. - It calls for the establishment of high-quality data sets and a collaborative development mechanism for computing power and electricity [32][33]. - The need for enhancing model capabilities and addressing issues related to data security and algorithm transparency is also emphasized [32][33]. Group 4: Implementation Measures - The document stresses the importance of organizational implementation, encouraging local energy authorities and enterprises to establish mechanisms for promoting AI in the energy sector [34][35]. - It advocates for collaborative innovation among enterprises, research institutions, and universities to build a robust ecosystem for AI and energy integration [34][35]. - The need for pilot demonstrations and the selection of replicable scenarios for AI applications in the energy sector is also highlighted [35][36].