近日，南方电网公司第七届电力调度AI应用大赛在广州落幕。在活动现场，南方电力调度控制中心依 托南方能源行业可信数据空间发布了电力调度高质量数据集。该批数据集可为智能调度、故障预警、新 能源消纳等业务数智化升级提供支撑，进一步丰富空间数据资源储备，为后续实现跨领域数据融合、协 同创新奠定了坚实基础。 筑基赋能 构建行业数据流通基础平台 场景驱动 跨域应用稳步推进 依托持续拓展的互联互通体系，该数据空间已联合贵阳、广州等城市数据空间及多家行业机构，初步建 立了跨空间、跨领域的数据互认互通机制，推动了电力、油气、交通等多行业数据安全有序流动。 南方电网数据平台与安全（广东）有限公司全力支撑南方电网公司建设运营全国首个能源行业可信数据 空间。空间于2025年7月作为能源行业首批且唯一单位，入选国家行业可信数据空间创新发展试点，同 时跻身国家数据基础设施建设第二批先行先试项目及国资央企领域可信数据空间系统建设试点，是南方 电网公司践行国家数据要素市场化战略的具体实践。 在场景应用方面，空间协同生态伙伴创新研发应用场景，覆盖电力看经济、绿色低碳、设备优化升级等 多元领域。例如，在"设备优化升级"场景中，通过融合设备运行与 ...

Core Insights - The National Petroleum and Natural Gas Pipeline Group (referred to as "National Pipeline") is focusing on utilizing over 10 billion core data points accumulated over five years of operation to enhance efficiency and safety in data usage and potential trading [2][3] - The initiative is part of a broader effort to integrate data resource development within state-owned enterprises, aiming to transform data into a marketable asset and address challenges related to data ownership, pricing, and circulation [3][12] Group 1: Data Utilization and Collaboration - National Pipeline is engaged in discussions to facilitate the use of its extensive data network, which includes production, transportation, and transaction information, to break market barriers and activate the industrial chain [2][3] - The State Data Bureau and the State-owned Assets Supervision and Administration Commission have initiated a pilot program involving 12 central enterprises, including National Pipeline, to explore collaborative data utilization with private enterprises and research institutions [2][4] Group 2: Challenges in Data Ownership and Valuation - A significant challenge identified is the ambiguity surrounding data ownership, which complicates the ability to classify data as an asset, particularly in relation to national energy security and user privacy [10][12] - The lack of clear ownership leads to difficulties in pricing and circulation of data, as companies struggle to establish fair market valuations without defined rights [12][13] Group 3: Technological Innovations and Solutions - Companies are adopting technologies such as blockchain and privacy computing to create "trusted data spaces" that allow for secure data circulation without transferring ownership [15] - The establishment of collaborative platforms, like China Mobile's "Huanxin Community," aims to create a closed-loop ecosystem for data sharing, joint research, and scenario co-creation [6][15] Group 4: Emerging Market Opportunities - The pilot program is expected to stimulate a new industry chain driven by data elements, with increased interest from enterprises in data asset registration and trading processes [17][18] - Small and medium-sized enterprises are benefiting directly from data-driven initiatives, such as credit support facilitated by large energy companies using consumer data [17][18] Group 5: Regulatory and Strategic Implications - The integration of data as a measurable and tradable asset poses new regulatory challenges, necessitating a shift in oversight from traditional asset management to include data capital management [18][20] - The evolving landscape of state-owned enterprise reform is being influenced by the potential of data to penetrate industry barriers and enhance operational efficiency [19][20]

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 National Bureau of Statistics of China is implementing a data efficiency enhancement initiative for state-owned enterprises, with 12 central enterprises as pilot leaders, aiming to improve data governance and resource utilization by 2027, benefiting over 100,000 SMEs [1][2] Group 1: Data Utilization and Management - State-owned enterprises are identified as key players in the development and utilization of data resources, with a focus on enhancing core competitiveness and promoting collaborative innovation in the industrial chain [1][2] - The initiative includes 10 key tasks centered around innovating data management mechanisms, fostering the data industry, enabling industrial transformation, and optimizing the innovation environment [2] Group 2: Collaboration and Innovation - The initiative encourages collaboration among state-owned enterprises and their partners across various sectors, including energy, transportation, and agriculture, to create a trusted data space and promote data sharing and innovation [2] - The National Oil and Gas Pipeline Group has created a comprehensive data network, aggregating over 10 billion core data entries, significantly improving data quality and operational efficiency in the natural gas supply chain [3] Group 3: Technological Integration - China Southern Power Grid has established a trusted data space that integrates advanced technologies like blockchain and privacy computing, enhancing data flow and collaboration among over 370 ecosystem partners [4] - China Machinery Industry Group has developed an "Agricultural Machinery Cloud" that connects the entire lifecycle of agricultural machinery, processing over 10 billion data entries daily [5] Group 4: Data-Driven Applications - China Mobile has created a big data platform that processes over 2000PB of core data, improving customer service and operational efficiency across various scenarios [6] - The China Automotive Technology and Research Center is focusing on carbon footprint accounting and data interoperability across the automotive supply chain, enhancing international rule recognition [6] Group 5: Future Directions - The initiative emphasizes the importance of enterprises taking the lead in data utilization, fostering multi-party collaboration, and integrating diverse data sources to drive industrial transformation and improve public welfare [6]

Core Viewpoint - The National Data Bureau has initiated a data efficiency enhancement action for state-owned enterprises, emphasizing collaboration among various stakeholders to maximize data utility and drive innovation [1][5]. Group 1: Data Efficiency Enhancement Action - The action was launched in July 2023, with 12 central enterprises designated as pilot leaders, collaborating with private companies, research institutions, and professional service organizations [1]. - The initiative focuses on three key areas: multi-party collaboration, multi-source data integration, and multi-field application expansion [2][5]. Group 2: Multi-Party Collaboration - The pilot encourages central enterprises to form cooperative alliances with other state-owned and private enterprises, research institutions, and third-party organizations to enhance data resource development and utilization [1][2]. Group 3: Multi-Source Data Integration - The pilot aims to promote data sharing and open access, requiring the 12 pilot central enterprises to create data service lists and integrate industry and government data for collaborative applications [2]. - Enterprises are encouraged to establish industry data standards and create trustworthy data spaces for secure and efficient data circulation [2]. Group 4: Multi-Field Application Expansion - The pilot encompasses traditional sectors like energy, transportation, and agriculture, as well as emerging fields such as satellite remote sensing and green technology [2]. - It emphasizes scenario-based applications, focusing on industry needs to develop high-value use cases and cross-industry collaborations [2]. Group 5: Case Studies from Pilot Enterprises - China Southern Power Grid has developed a trusted data space using advanced technologies, resulting in a tenfold increase in ecosystem partners and a threefold increase in collaboration demands within nine months [3]. - China Mobile has integrated various data sources to support emergency management, enhance industry upgrades, and improve public services, benefiting over 100 million people [4]. Group 6: Future Expectations - The initiative aims to enhance data governance capabilities and significantly improve data resource utilization and sharing by 2027, benefiting over 100,000 small and medium-sized enterprises [5].

Core Points - The establishment of the Trusted Data Space Development Alliance aims to accelerate the construction and development of a data-driven digital economy [4][5] - The alliance will serve as a platform for policy implementation, ecological collaboration, and innovation dissemination, focusing on national strategic directions [4][5] - The alliance is guided by the National Data Bureau and includes participation from various central enterprises and research institutions, emphasizing cross-industry collaboration [8] Industry Developments - The National Data Bureau's "Trusted Data Space Development Action Plan (2024-2028)" aims to establish over 100 trusted data spaces by 2028, promoting data space solutions and best practices [9][10] - The Southern Power Grid has initiated the construction of a trusted data space for the energy sector, with plans to optimize data resource allocation and utilization [10][11] - By December 31, 2024, the Southern Energy Industry Trusted Data Space is set to begin trial operations, supporting multiple energy data circulation application scenarios [10][11]