12月30日，由中国南方电网有限责任公司(以下简称"南方电网公司")主办的数字电网技术装备现代产业链共链行动大会并南网数字（301638）集团2025数 智赋能技术交流暨媒体见面会在北京举行。本次大会以"数智赋能，共创数字电网现代产业新篇章"为主题，聚焦新型电力系统和数字中国建设关键需求， 系统推进数字电网技术装备协同创新和规模化应用，充分发挥央企产业链"链长"牵引带动作用，促进创新要素、产业资源和应用场景高效联动，加快构建 安全可控、开放共赢的数字电网现代产业体系。 数智赋能主旨演讲嘉宾一致认为，当前新一轮科技革命和产业变革深入推进，数字技术与能源电力融合发展已成为构建新型电力系统的重要路径。南方电 网公司立足数字电网建设实践，持续强化关键核心技术攻关和共性能力平台建设，以人工智能等新一代信息技术为牵引，深化场景牵引、能力开放和生态 共建，通过共链行动促进产业链上下游协同创新、融通发展，加快构建安全可控、开放共赢的数字电网现代产业生态。 本次大会集中发布共链行动计划和供需对接清单，系统展示南方电网公司在数字电网、人工智能、电碳算协同、可信数据空间等领域的阶段性成果，进一 步搭建开放、协同的产业合作平台。其中 ...

21世纪经济报道记者费心懿 北京报道 新一轮科技革命和产业变革深入推进，人工智能等新一代信息技术正从单点应用走向系统赋能，数字技 术与能源电力——这一"比特与瓦特"的融合发展已成为构建新型电力系统的重要路径。 在加快推进产业链融通发展的背景下，如何通过能力开放和场景共建，推动数字电网技术装备产业链协 同升级，成为行业普遍关注的重点方向。 近日，数字电网技术装备现代产业链共链行动大会及南网数字集团2025数智赋能技术交流会在北京召 开，大会上，主办方南方电网交出了这一问题的"南网答案"。 活动主办方南方电网正立足数字电网建设实践，持续强化关键核心技术攻关和共性能力平台建设，以人 工智能等新一代信息技术为牵引，深化场景牵引、能力开放和生态共建，通过共链行动促进产业链上下 游协同创新、融通发展，加快构建安全可控、开放共赢的数字电网现代产业生态。 南方电网数字电网研究院股份有限公司党委委员、副总经理郭晓斌介绍，南方电网公司深入实施产业链 融通发展共链行动，以"阳光共链"平台聚合超247家单位参与，构筑技术完备、自主可控的数字电网生 态圈。在资源共享方面，能源行业可信数据空间入选国家级试点，实现跨行业数据产品上架与场景 ...

电力行业人工智能应用迈入规模化、体系化、生态化发展的新阶段，为推动产业链上下游 协同创新注入强劲动能。 12月30日， 由中国南方电网有限责任公司（以下简称 "南方电网公司"）主办的数字电 网技术装备现代产业链共链行动大会 并南网数字集团 2025数智赋能技术交流暨媒体见 面会 在北京举行 。本次大会以 "数智赋能，共创数字电网现代产业新篇章"为主题， 聚 焦新型电力系统和数字中国建设关键需求，系统推进数字电网技术装备协同创新和规模化 应用，充分发挥央企产业链 "链长"牵引带动作用，促进创新要素、产业资源和应用场景 高效联动，加快构建安全可控、开放共赢的数字电网现代产业体系 。 数智赋能 主旨演讲 嘉宾一致认为 ，当前新一轮科技革命和产业变革深入推进，数字技 术与能源电力融合发展已成为构建新型电力系统的重要路径。南方电网公司立足数字电网 建设实践，持续强化关键核心技术攻关和共性能力平台建设，以人工智能等新一代信息技 术为牵引，深化场景牵引、能力开放和生态共建，通过共链行动促进产业链上下游协同创 新、融通发展，加快构建安全可控、开放共赢的数字电网现代产业生态 。 本次大会集中发布共链行动计划和供需对接清单，系统 ...

Core Insights - The company aims to empower high-quality energy development through AI integration, focusing on practical outcomes from policy requirements [1] - The integration of AI with energy and power sectors is seen as a significant innovation, enhancing the synergy between electricity and carbon management [2] Group 1: AI and Energy Integration - The company is accelerating the construction of an "electric-carbon-computing" system to address challenges posed by the integration of data and power transmission projects [2] - A four-dimensional testing matrix has been developed to achieve a 95% accuracy rate in predicting power consumption for computing resources [2] - The company has created a real-time power-computing measurement system, successfully tested in Guangzhou, which aims to make computing resource usage as convenient and quantifiable as electricity [2][3] Group 2: Data Activation and Value Release - The company is leveraging AI to break down data barriers and activate dormant energy data resources, establishing a complete data value release chain [4] - A data asset management platform has been established to facilitate the regular collection and monitoring of vast amounts of data, with plans to launch a trusted data space in August 2024 [4] - The company has collaborated with over 280 ecosystem entities to create high-value application scenarios, enhancing data accessibility and utilization [4] Group 3: AI-Driven Operational Efficiency - The "electric-carbon-computing collaborative operation system" developed by the company acts as an intelligent navigation tool for power consumption and carbon emissions monitoring [3] - This system has enabled a reduction of over 10% in computing operation costs by dynamically adjusting tasks based on electricity price fluctuations [3] - The company has achieved a 100% green electricity supply for all venues at the Guiyang International Big Data Industry Expo, significantly reducing coal consumption and carbon emissions [3] Group 4: Ecosystem and Technological Innovation - The company is focusing on building a robust AI technology foundation, with proprietary models enhancing simulation and optimization capabilities [7] - The "Da Watt" series of models has been recognized for its superior performance in simulating power system operations, significantly improving analysis speed and accuracy [7] - The company has invested in a scalable computing capacity of nearly 1400 PFLOPS, supporting its ongoing technological advancements [7] Group 5: Practical Applications and Impact - AI has enabled the company to achieve a 97% renewable energy consumption rate, positioning it among the top in the country [8] - The company has conducted the largest cross-provincial vehicle-grid interaction experiment in the country, involving over 100,000 electric vehicles [8] - AI-driven interventions in urban power management have led to a 43% reduction in average power restoration times, enhancing public satisfaction [8]

Core Insights - The integration of digital and energy revolutions is driving a significant increase in demand for computing power, with projections indicating an average annual growth rate of around 20% in China's data center electricity consumption from 2024 to 2030, outpacing the overall electricity consumption growth rate [1] Group 1: Industry Developments - The 2025 China International Big Data Industry Expo highlighted discussions on promoting the collaborative development of electricity and carbon computing [1] - The Deputy Director of the National Data Bureau emphasized that electricity supply is a critical factor influencing computing power development, and the scale of computing power directly affects data processing efficiency [1] - The rapid advancement of AI is leading to an explosive growth in computing power demand, necessitating the establishment of a new infrastructure that integrates data, computing, networks, and energy [1] Group 2: Southern Power Grid's Innovations - Southern Power Grid showcased its developed Electric-Carbon-Computing Collaborative Operation System, which is based on power infrastructure and promotes the economic and green flow of computing resources [2] - The system features three core capabilities: real-time monitoring of power consumption, dynamic scheduling to reduce operational costs by over 10%, and nationwide collaboration to connect computing resources with the integrated national computing network [2] - The system aims to break down information barriers between electricity, computing power, and carbon emissions, achieving precise matching and efficient scheduling [2] Group 3: Practical Applications and Future Outlook - The Electric-Carbon-Computing Collaborative Operation System has shown initial success, with a case where a computing task was migrated to a data center, resulting in a 10% reduction in overall computing costs and the consumption of 113.4 kWh of green electricity [3] - The flexibility of computing power scheduling is identified as a crucial foundation for collaborative operations, requiring solutions for application, data, and model coordination [3] - Future expectations include making the use of computing resources as convenient and quantifiable as water and electricity, necessitating the establishment of a precise measurement system for computing power [3]

Core Viewpoint - The launch of China's first electric-carbon computing collaborative operation system aims to optimize the real-time interaction between electricity, computing power, and carbon emissions, contributing to energy saving and carbon reduction in data centers [1][3]. Group 1: System Functionality - The electric-carbon computing collaborative operation system integrates "power grid, computing network, and communication network" to enhance operational efficiency [1]. - The system automatically schedules computing tasks to western regions when cheaper electricity prices are available, and utilizes green energy when renewable energy generation is abundant [1]. Group 2: Industry Impact - By 2030, China's computing power energy consumption is expected to reach 4,800 billion kWh, with carbon emissions exceeding 200 million tons [3]. - A reduction of 0.1 yuan in comprehensive electricity costs for computing power could save the industry 48 billion yuan annually, benefiting end users [3]. - Increasing the use of green electricity by 1% could reduce carbon emissions by approximately 2 million tons per year, equivalent to planting 110 million trees [3].