挑战即机遇，电力工程面临"收益不确定性"与"成本控制"双重压力 吉雅图指出，尽管"十五五"期间全社会用电量将持续增长，新能源装机占比已超45%，但以136号文为 代表的电力电价市场化的影响和冲击，项目在收益不确定性、运营复杂性，包括成本控制和技术创新的 压力和挑战陡然增加，倒逼企业重新审视项目全生命周期收益。 痛点聚焦：项目收益波动、并网限制、技术迭代加速、建设期质量安全风险叠加，导致"增量不增利"困 局。 转自：新华财经 9月24日，由中国电力企业联合会大数据与统计分会主办，广联达科技股份有限公司承办的"2025新型电 力系统数智发展论坛"平行论坛成功举办。论坛以"数字电力 AI启航"为主题，来自政府部门、电力企事 业单位、研究机构、高等院校、科技公司等单位的领导、专家及代表齐聚一堂，聚焦数智技术与新型电 力系统深度融合，共探能源绿色发展新路径，为助力"双碳"目标和能源电力高质量发展贡献智慧和力 量。 广联达副总裁吉雅图受邀以"前沿AI与数智技术在能源发电的创新应用"为主题进行演讲。广联达副总裁 吉雅图在平行论坛上指出，"一体化数智平台+AI场景化深耕" 正成为行业从"规模扩张"转向"价值创 造"的关键引擎 ...

构建全链条科创体系 本报记者 马宇薇 当前，新能源行业的竞争已不再局限于规模扩张的单一维度，而是转向以科技创新破解"效率瓶 颈"与"技术壁垒"的深层较量。 作为中国新能源行业的领军企业、国家能源集团新能源板块核心上市平台，龙源电力集团股份有限公司 （以下简称"龙源电力"）在"十四五"期间始终秉持"创新是企业的责任"这一核心理念，用全链条创新体 系筑牢根基、以"擎源"大模型重塑行业生态、借助多元实践拓宽应用边界，不仅交出了新质生产力培育 的亮眼答卷，更成为能源行业智能化转型的"领航者"。 近日，中国上市公司协会联合《证券日报》等媒体启动"我在'十四五'这五年 上市公司在行动"主题活 动，探寻龙源电力如何以创新之笔绘就绿色未来。 筑基： 让技术突破落地为产业实效，从来不是实验室里的"孤芳自赏"，而是从研发到应用的"全链条贯通"。龙 源电力深谙此道，在"十四五"期间依托"1+1+4+N"创新体系，搭建起平台、人才、成果转化环环相扣的 创新生态，让每一项技术突破都能精准对接产业需求，真正转化为推动发展的"生产力引擎"。 建设国家能源局授牌的研发平台——国家能源风电运营研发（实验）中心，发展壮大新能源生产运营、 新型电 ...

Core Insights - Artificial intelligence is accelerating the global energy transition and sustainable development, with state-owned enterprises (SOEs) playing a crucial role in integrating AI into the energy sector [1][2][4] Group 1: AI Integration in Energy Sector - SOEs are driving the integration of AI in various energy sectors, including oil, nuclear, coal, and electricity, aiming to create replicable and high-value application scenarios [1][2] - The application of AI in the energy sector is still in its early stages compared to other industries like military, but the complete industrial chain and diverse application scenarios provide a competitive advantage for rapid development [2][4] - AI's core value lies in deep coupling with application scenarios, maximizing data value, and promoting systemic transformation across the energy supply chain [3][4] Group 2: Practical Applications and Achievements - In oil and gas exploration, AI applications have shown significant advancements, such as the high accuracy of AI in drilling analysis and improved bidding success rates [4][5] - AI is enhancing efficiency in the electricity sector, with notable improvements in load forecasting accuracy and operational decision-making speed [4][5] - In the nuclear sector, AI supports high-quality construction and safety management by identifying technical discrepancies in project documentation [4][5] Group 3: Challenges and Future Directions - Despite progress, the energy sector faces challenges such as data security, cost pressures, and technological reliability, necessitating collaborative efforts to overcome these hurdles [6][7] - The need for a robust digital ecosystem involving government, industry, academia, and research institutions is emphasized to facilitate the intelligent transformation of the energy sector [7] - A new research initiative has been launched to develop high-value AI scenarios across the entire energy industry chain, focusing on scientific discovery, intelligent scheduling, and green low-carbon practices [7]

Core Points - The meeting between Shanxi Provincial Government and CRRC Group focused on high-quality development and modernization in Shanxi [1] - Both parties aim to enhance cooperation in various fields including rail transit equipment, green transportation, high-end motor manufacturing, new energy equipment, and AI+energy [1] - A specialized mechanism will be established to strengthen communication and project implementation, aligning with the 14th Five-Year Plan and promoting joint scientific research [1] Group 1 - The meeting was attended by key officials from both Shanxi Province and CRRC Group, including the provincial governor and the chairman of CRRC [1] - The collaboration will focus on comprehensive energy solutions and complete equipment supply [1] - Emphasis will be placed on technological innovation to drive industrial innovation and energy transition [1]

Core Viewpoint - The article emphasizes the importance of integrating artificial intelligence (AI) into the energy sector to enhance high-quality development and support the construction of a new energy system [2][3][10] Group 1: Strategic Guidance - The release of the "Implementation Opinions" provides a strategic direction for the energy sector to seize opportunities in AI development and promotes deep integration of AI with energy [3][4] - AI is recognized as a key driver for a new round of technological revolution and industrial transformation, making the integration of AI and energy a systemic change that requires careful planning and execution [5] Group 2: Application Focus - The article highlights the need for high-value application scenarios in the energy sector, identifying eight key areas for AI application, including AI in power grids and renewable energy [6] - The focus on application aims to address common bottlenecks in the industry, such as insufficient high-value scenarios and low resource sharing, thereby facilitating the implementation of AI in energy [6] Group 3: Practical Exploration - The Southern Power Grid Company has proactively engaged in AI practices, establishing significant infrastructure and launching the first self-controlled large model "Dawatt" to support the new power system and energy framework [7][8] - The company has planned over 350 application scenarios across various business domains, significantly enhancing the effectiveness of energy services [8] Group 4: Key Technology Supply - The article stresses the importance of core elements such as computing power, data, and models for the development of AI in the energy sector, advocating for self-reliance and innovation [9] - The establishment of a fully autonomous computing cluster and high-quality data sets is crucial for supporting AI innovation in the power sector [9] Group 5: Future Vision - The Southern Power Grid aims to embrace AI comprehensively, leveraging its advantages in digital transformation and data assets to create a "digital grid intelligence" that promotes efficient human-machine collaboration [10] - The company seeks to contribute to national AI innovation and provide solutions for global energy transition towards a green and sustainable future [10]

Core Viewpoint - The 2025 36Kr Industry Future Conference in Xiamen, China, focuses on five key sectors: artificial intelligence, low-altitude economy, advanced manufacturing, new energy, and large consumption, aiming to address industry challenges and explore development paths [1] Group 1: Conference Overview - The conference is co-hosted with the Ministry of Commerce and emphasizes high standards and value [1] - It aims to integrate national strategic guidance with industry development, focusing on collaboration among government, capital, and industry [1] - A roundtable discussion on "How to Navigate New Energy Investment Amidst Overcapacity" features prominent investors discussing challenges in the energy sector [1] Group 2: Roundtable Insights - The roundtable highlights the rapid development of the new energy sector, which is now facing overcapacity and intensified price wars [3][4] - Investors express a long-term optimistic outlook for the new energy industry despite current challenges [12][11] - The discussion reveals that overcapacity is primarily a structural issue concentrated in the manufacturing sector, with ongoing demand for energy driven by AI and computing needs [8][9] Group 3: Investment Strategies - Investment strategies are shifting towards projects with advanced technology and resilient growth potential, focusing on cost reduction and efficiency improvements [10][11] - Investors emphasize the importance of understanding customer needs and market dynamics for successful commercialization of technologies [19] - The focus is on identifying mature projects with established revenue streams to mitigate risks associated with early-stage investments [20] Group 4: Future Outlook - The consensus is that the overcapacity phase is nearing an end, with potential for recovery and new investment opportunities [22] - Successful companies in the future will need to demonstrate technological innovation, effective cost management, and internationalization capabilities [26][27] - Investment firms aim to play a supportive role in industry consolidation and provide necessary resources to help companies thrive [27]

Core Viewpoint - Qiniu Intelligent (2567.HK) has entered into a strategic partnership with Wuxiang Cloud Valley to scale AI inference computing power, targeting the trillion-dollar AI inference computing market [1] Group 1: Strategic Partnership - The collaboration aims to provide accessible AI inference computing power for enterprises and entrepreneurs [1] - Both companies will explore vertical fields such as AI + education and AI + energy [1] Group 2: Product Offerings - Qiniu Intelligent currently has three product lines: Media Cloud, AI Cloud, and LinX Cloud, with a new focus on AI inference computing products [1] - The launch of LinX AI in August signifies Qiniu's comprehensive layout from cloud to edge, expanding into the smart hardware AI market [1] Group 3: Market Demand - As of August, Qiniu Intelligent's developer community has exceeded 1.69 million, with a continuous increase in new registrations [1] - The demand for AI computing power is rising, and the partnership will enable Qiniu to offer refined large model AI inference and computing power leasing services [1] - This collaboration is expected to lower the development threshold for AI applications, significantly shortening the cycle from concept validation to large-scale commercialization [1]

清晨，内蒙古的风电场里，人工智能算法已精准预测出未来一段时间的风速与发电量；千里之外的华东智能电网，正实时 平衡着海量用电需求与分布式能源的供电波动；在深海油气平台，AI驱动的监测系统持续排查设备隐患，确保开采作业安 全稳定……这幅由人工智能深度赋能的能源图景，正从蓝图加速走向现实。 近日，国家发展改革委、国家能源局联合印发《关于推进"人工智能+"能源高质量发展的实施意见》（以下简称《实施意 见》），为能源与AI的深度融合划定了科学路径。新政标志着我国能源行业正迈入一场系统性、革命性变革——以AI为核 心驱动力，重塑能源生产、传输、消费全链条，为构筑高质量能源供给体系与高水平能源安全屏障奠定坚实基础。 《实施意见》为我们绘制了一幅清晰的路线图：到2027年，能源与人工智能融合创新体系初步构建，算力与电力协同发展 根基不断夯实，人工智能赋能能源核心技术取得显著突破。届时，5个以上专业大模型将在电网、发电、煤炭、油气等行业 深度应用，探索出百个典型应用场景赋能路径。这一切，将为我国能源领域智能化发展奠定坚实基础，让智能化成效初 显。 展望2030年，能源领域人工智能专用技术与应用总体将达到世界领先水平。到那时，我 ...

清晨，内蒙古的风电场里，人工智能算法已精准预测出未来一段时间的风速与发电量；千里之外的华东 智能电网，正实时平衡着海量用电需求与分布式能源的供电波动；在深海油气平台，AI驱动的监测系 统持续排查设备隐患，确保开采作业安全稳定……这幅由人工智能深度赋能的能源图景，正从蓝图加速 走向现实。 对于"双碳"目标，"AI+能源"是不可或缺的加速器。高比例新能源的接入是绿色转型的关键，但风能、 太阳能的间歇性、波动性，曾让电网"望而生畏"。如今，AI风光功率预测模型可精准预判新能源出力， 为电网接纳新能源提供技术支撑；在综合智慧能源领域，AI可统筹协调分布式光伏、储能、充电桩等 设备，提升能源利用效率。 "AI+能源"还会催生全新产业模式与价值链条。虚拟电厂通过AI整合分散的储能、电动汽车资源，成为 电网的"灵活调节池"；能源服务平台借助AI分析用户用电习惯，提供个性化节能方案……这些新模式不 仅将重塑能源产业格局，更让能源从"单一商品"转变为"综合服务"，为行业开辟新增长空间。 推进"AI+能源"深度融合，仍需啃下多个"硬骨头"。能源数据分散在不同企业、不同部门，标准不一、 共享不畅；部分AI技术在能源场景的可靠性尚需 ...

清晨，内蒙古的风电场里，人工智能算法已精准预测出未来一段时间的风速与发电量；千里之外的 华东智能电网，正实时平衡着海量用电需求与分布式能源的供电波动；在深海油气平台，AI驱动的监 测系统持续排查设备隐患，确保开采作业安全稳定……这幅由人工智能深度赋能的能源图景，正从蓝图 加速走向现实。 近日，国家发展改革委、国家能源局联合印发《关于推进"人工智能+"能源高质量发展的实施意 见》(以下简称《实施意见》)，为能源与AI的深度融合划定了科学路径。新政标志着我国能源行业正迈 入一场系统性、革命性变革——以AI为核心驱动力，重塑能源生产、传输、消费全链条，为构筑高质 量能源供给体系与高水平能源安全屏障奠定坚实基础。 《实施意见》为我们绘制了一幅清晰的路线图：到2027年，能源与人工智能融合创新体系初步构 建，算力与电力协同发展根基不断夯实，人工智能赋能能源核心技术取得显著突破。届时，5个以上专 业大模型将在电网、发电、煤炭、油气等行业深度应用，探索出百个典型应用场景赋能路径。这一切， 将为我国能源领域智能化发展奠定坚实基础，让智能化成效初显。 展望2030年，能源领域人工智能专用技术与应用总体将达到世界领先水平。到那时 ...