同力日升深耕电梯配套行业多年，是国内外知名电梯主机厂的核心配套产品供应商，在综合配套能力、 技术研发实力、优质客户资源、一体化经营模式及全国性服务网络等方面具备较强竞争优势。报告期 内，公司主动调整生产备货节奏，持续优化产品结构，通过积极拓展扶梯部件客户，有效抵消房地产下 行带来的行业直梯销量下滑影响；同时，公司积极响应电梯行业政策导向，把握电梯"以旧换新"政策机 遇，推动电梯部件业务市场占有率稳步提升，确保核心电梯业务稳健发展。 在巩固电梯主业的基础上，同力日升还通过控股北京天启鸿源新能源科技有限公司(以下简称"天启鸿 源")切入新能源领域，形成"电梯+新能源"双轮驱动格局。据公司工作人员介绍，2025年上半年，天启 鸿源经营业绩表现亮眼，实现净利润1.64亿元，同比增长42.36%。项目推进方面，公司上半年成果丰 硕。天津铭源嘉旺100MW风电项目成功并网发电；承德航天鸿源300MW风场项目并网规模持续扩大； 承德天启鸿源围场920MWh共享储能电站项目正式投入运营并贡献容量租金收入；广东肇庆怀集 600MWh网侧独立储能项目完成签约；遵义绥阳600MWh构网型新型独立储能电站项目获得电网接入批 复，具备 ...

8月27日晚间，同力日升（605286）发布2025年半年报，上半年，公司实现营业收入11.22亿元，归属于 上市公司股东的净利润1.16亿元；实现经营活动产生的现金流量净额1.98亿元，同比增长169.16%。同 力日升把握行业发展趋势，对算电协同加大投入力度，与壳牌中国共推浸没式液冷储能技术，新能源业 务快速发展，控股子公司天启鸿源上半年实现净利润1.64亿元，同比增长42.36%。 同力日升是全国生产电梯部件产品的重点骨干企业，公司深耕电梯配套行业多年，是迅达、奥的斯、蒂 森克虏伯、通力、日立、西奥等国内外知名电梯主机厂的配套产品供应商，在综合配套、技术研发、客 户资源、一体化经营、服务网络等方面具有较强的竞争优势。上半年，公司积极应对房地产持续低迷和 大宗原材料波动风险，主动调整备货节奏，持续优化产品结构，积极拓展扶梯部件客户以抵消房地产下 行带来的整体行业直梯销量下行。同时，积极响应电梯行业政策，把握以旧换政策机遇，实现电梯部件 业务市占率稳步增长，电梯业务稳健发展。 同力日升通过控股天启鸿源进入新能源领域，上半年，天启鸿源营业收入3.42亿元。上半年，天津铭源 嘉旺100MW风电项目成功并网，承德 ...

8月24日，2025年中国算力大会落下帷幕，"绿色低碳"和"智能敏捷"成为高频关键词，人工智能的飞速 发展正在重塑算力基础设施，而算力的进化又反向推动AI迈向新的高度。电算协同成为时代之需，多 项与"算电协同"相关的技术和规划密集发布。 《2025算电协同技术白皮书》系统剖析了算电协同的背景、架构、技术和场景，为数字经济与能源革命 融合提供路径；中国移动发布"算网大脑3.0"引入AI大模型管理AI算力。从"简单拼凑"跨向"智能协 同"，中国算力产业正从规模扩张向高质量发展转化，对AI新基建的模式提出了新要求，也为具备前瞻 性布局的企业提供了新的历史机遇。 山高控股（00412.HK）凭借"电算一体化"超前布局，为新兴产业和未来产业提供稳定、可靠、高效的 绿色算力供给，顺利完成从产业投资者到AI时代"绿色算力基建生态构建者"的战略跃迁。 从产业投资到"绿色智算供给者" 此前，包括北京、上海、新加坡和美国弗吉尼亚州在内的多个地区，均对数据中心的PUE和绿电消纳比 例提出了明确要求，不符合标准的新项目将难以备案或获得扩容。 在监管红线收紧的当下，该项目为行业提供了一份具备"合规通行证"的解决方案，被列入中国信息通信 ...

近期，全国首个数据中心源网荷储一体化绿电直供项目——乌兰察布数据中心低碳算力基地源网荷储一 体化项目正式投运。该项目通过风光发电、智能输电、并网直供和储能调峰等系统协同运行，实现了清 洁能源与数据中心的直接供能对接。 面临经济性挑战。张林山说，新能源出力的波动性与算力需求的稳定性之间存在着冲突。在西部，"极 热无风""日落无光"等特殊时段，风力发电和光伏发电会出现骤降的情况，这对需要稳定电力供应的数 据中心来说是巨大的挑战。为了保障算力的稳定运行，数据中心不得不额外配置储能设备或火电作为备 用电源，这一举措导致边际成本大幅上升，加剧了运营压力。同时，跨省绿电交易壁垒加重了成本负 担，东部企业若想采购西部的绿电，需要承担跨省输电费、政府基金等一系列附加成本，使得绿电实际 到网价格比本地火电高出不少，影响了东部企业采购西部绿电的积极性，阻碍了绿电资源在全国范围内 的优化配置。 还需更多价格信号和激励机制。钟洪麟认为，新能源发电的绿色价值如碳减排、生态效益等尚未通过价 格信号得到充分体现，其低碳优势难以转化为市场竞争力，而碳市场机制目前对人工智能、数据中心等 新兴高耗能行业的覆盖尚不完善，绿色消费激励机制不足。尽管 ...

" 我今天做的事跟当初想做的事，没有差别。" 一头长发随性披着，身穿宽松的黑色半袖上衣、深蓝色紧身牛仔裤、以及黑色的皮靴，远远看去，这样靠 在沙发一角的居静，仿佛是艺术的、自由的。谁都很难将这样的形象与"能源""算力装备""基础设施"这些 重资产词汇联系在一起，但事实上，过去二十年， 他亲身经历、甚至推动了国内算力基础设施行业的历次 变革。 " 占算力链条成本不到3%的IDC，供需错配只因不懂用户。 " 作者丨赵之齐 编辑丨胡敏 上世纪九十年代，早在国内数据中心建设还是一片荒原时，居静便踏入其中，带领团队从0到1建立了宁夏 中卫、张家口张北的第一个数据中心，且深度参与鄂尔多斯、张家口和大同的城市算力规划。 此外，他也是曾经的"美股明星"—— 秦淮数据的创始人 。 十多年前，在给互联网大厂交付数据中心时，居静就发现一个行业现实：很多企业把数据中心当成"商誉 工程"，在享受到资本市场带来的商誉变现后，便不再真正投入精力去打磨需要长期精耕细作的算力基础 设施。 这种想法固然美好，但需要足够的定力、愿力以及财力。不可或缺的，还有"地利"——一个 尚未过度商 业化、能源特性完整、且物理距离靠近用户侧的城市。 最终，他作 ...

Core Viewpoint - The article discusses the emergence of a new business model in the AI industry, specifically focusing on the success of a startup, Gongji Technology, which has effectively commercialized the concept of shared computing power, addressing the growing demand for AI inference capabilities [4][6]. Group 1: Market Demand and Trends - The year 2025 is anticipated to be a pivotal year for AI Agents, leading to a significant increase in demand for AI inference computing power, with IDC predicting that the workload share of inference servers will rise from 51.5% in 2020 to 62.2% by 2026 [4]. - The demand for AI services has led to the emergence of various AI companies, including those focused on video generation and companion robots, which face challenges related to high long-term server rental costs from cloud providers [5][6]. Group 2: Business Model and Innovation - Gongji Technology offers a flexible computing power service that allows users to pay based on actual usage, addressing the need for stable and elastic computing resources [6][30]. - The company has developed a unique model that treats the city as a large distributed data center, where idle computing resources from individual users can be matched with AI companies needing processing power [7][30]. - The startup has achieved a stability rate of over 99.9% in its service, allowing for seamless transitions between idle computers for task execution [7][23]. Group 3: Company Background and Growth - Gongji Technology was founded by a team of young entrepreneurs, including a dropout from a PhD program, who identified a significant market need for shared computing resources after experiencing challenges in their own research [8][9]. - The company has successfully transitioned from a consumer-focused model to serving B2B clients, generating over 20 million yuan in revenue in the first half of 2023, primarily from business clients [8][70][71]. Group 4: Challenges and Solutions - The company faced skepticism from investors due to the historical challenges of monetizing shared computing power, which had not been successfully achieved in the past [16][18]. - Gongji Technology has navigated technical challenges by iterating its product over 80 times to ensure ease of use for individuals sharing their computing power [7][30]. Group 5: Future Outlook - The company is positioned to participate in national-level infrastructure projects, indicating a growing recognition of the importance of shared computing resources in the AI landscape [22][35]. - The founders believe that the future of computing power will increasingly rely on flexible, on-demand services rather than traditional long-term rentals, which are often inefficient for fluctuating AI workloads [29][30].

Investment Rating - The report assigns a "Buy-A" investment rating with a target price of 45.45 CNY for the next six months [4][6]. Core Insights - The company has successfully transformed its business model, with significant growth in its new energy sector, which now serves as a key growth driver, surpassing traditional elevator business revenue [1][21]. - The implementation of the 136 document is expected to enhance the value of energy storage, with the introduction of a capacity price mechanism in Gansu province, which could be adopted nationwide, providing stable revenue for the energy storage industry [2][54]. - The company is strategically positioned to benefit from the green electricity revolution driven by the surge in AI computing power, with initiatives in data centers and green energy projects [3][55]. Summary by Sections 1. Dual Business Model Driving High-Quality Development - The company has diversified into the new energy sector through the acquisition of Beijing Tianqi Hongyuan, focusing on energy storage system integration and new energy power station development [15][16]. - In 2024, the new energy business revenue grew by 103.61% to 879 million CNY, accounting for 34.76% of total revenue, with a gross profit contribution of 64.75% [21][28]. - The company has successfully balanced the cyclical fluctuations of the elevator industry by expanding its new energy business [21][28]. 2. Policy-Driven Energy Storage Value Recovery - The cancellation of mandatory energy storage requirements is expected to shift the industry from price competition to product quality competition [40][51]. - Gansu province has introduced a capacity price mechanism for independent energy storage, which is anticipated to stabilize investment returns and promote sustainable development in the energy storage sector [54][55]. 3. Integrated Energy Supply Solutions - The increasing energy consumption of data centers, driven by AI, presents a significant opportunity for energy storage solutions [55][56]. - The integration of green electricity supply and independent energy storage is expected to create a synergistic revenue model, enhancing profitability for energy projects [63][64]. 4. Proprietary Technology and Product Barriers - The company has established a strong product barrier through self-developed technologies and a decade of industry experience, focusing on high reliability and energy efficiency in its energy storage products [66][68]. - The company holds 39 patents related to energy storage and has made significant investments in R&D, ensuring a competitive edge in the market [68].

Core Insights - The collaboration between OpenAI and Oracle to develop an additional 4.5GW of data center capacity reflects a significant shift in the operational logic of the AI industry, moving towards a model where computing power is treated as a flexible service rather than a fixed asset [1][3][6] Group 1: Collaboration Details - OpenAI and Oracle's partnership is not merely a commercial agreement but represents a deep integration of technology and infrastructure services, allowing for enhanced power distribution and disaster recovery capabilities across multiple regions [4][13] - The collaboration enables OpenAI to reduce operational costs by leveraging Oracle's efficient data center infrastructure, which maintains a Power Usage Effectiveness (PUE) of below 1.2, significantly better than the industry average of 1.5 [5][6] Group 2: Computing Power Supply Model - The partnership signifies a paradigm shift in the computing power supply model, moving from reliance on self-built data centers to a more flexible, service-oriented approach, akin to the transition from private generators to public power grids [3][4] - The scale of operations, with the ability to run over 2 million chips, enhances both companies' influence in the semiconductor supply chain, challenging the dominance of Nvidia in the AI chip market [7][9] Group 3: Energy and Computing Synergy - The 4.5GW data center capacity requires substantial energy, equivalent to the annual electricity consumption of 3.15 million households, highlighting the need for efficient energy management in modern data centers [10] - Schneider Electric's report emphasizes the necessity for a dynamic synergy between energy supply and computing power, advocating for a holistic approach to energy management that integrates power supply, computing loads, and cooling systems [10][11] Group 4: Geopolitical Implications - The collaboration aligns with U.S. government initiatives to maintain leadership in advanced computing infrastructure, indicating that the partnership extends beyond commercial interests into national strategic considerations [13][15] - The intertwining of commercial cooperation and national strategy suggests a blurred line between public and private sectors in the context of AI infrastructure, as the U.S. seeks to consolidate computing resources for competitive advantage in the global AI landscape [15][16]

Core Insights - Schneider Electric showcased its leadership in AI technology at the WAIC 2025, emphasizing the theme "Intelligent Connection and Collaborative Impact" [1][2] - The company aims to drive digital and green transformation across various industries in China through technological and ecological innovation [2][4] Group 1: AI Technology and Industrial Transformation - AI technology is rapidly evolving, with its large-scale application expected to drive structural changes in key sectors such as energy and industry, unleashing significant technological innovation [4] - Schneider Electric has been deeply engaged in machine learning and AI algorithms for over 20 years, launching AI applications tailored to energy management and industrial automation [4][7] Group 2: Lighthouse Factories and AI Applications - Schneider Electric's "Lighthouse Factories" demonstrate successful AI applications: the Shanghai Putuo factory achieved an 82% increase in per capita production efficiency, while the Wuxi factory reduced carbon emissions by 90% through AI-driven solutions [7] - The company is integrating AI technology into digital and green solutions across critical industries, including packaging, oil and gas, data centers, smart buildings, and future power grids [7] Group 3: Product Innovations - The EcoStruxure™ Edge Intelligence Box was launched to enhance data collection, management, real-time computation, and intelligent decision-making in industrial settings [8] - The EcoStruxure™ Building GPT, an AI agent, was introduced to improve HVAC operations and energy efficiency in smart buildings [13] - Schneider Electric unveiled the EcoStruxure™ Energy Operation system, designed for comprehensive power management in China, covering low and medium voltage distribution and microgrid monitoring [16] Group 4: Reports and Research - The company released a report titled "Computing Power and Electricity Collaboration: Challenges and Solutions for Data Centers," addressing the pressures of power stability, cost control, and carbon emissions management in the face of rising computing demands [22] - Another report, "AI: The Core Force Driving a Sustainable Future," highlights AI's transformative potential in key sectors [25] Group 5: Ecosystem and Partnerships - Schneider Electric is expanding its "AI + Industry" ecosystem in China, collaborating with developers, system integrators, and research institutions to foster innovation [28] - The company has initiated the "Winning Plan" to accelerate the application of cutting-edge digital technologies, focusing on the "AI + Industry" track for sustainable development [37] Group 6: Industry Insights and Future Directions - The company emphasizes that AI technology is a core engine driving new quality transformation in industries, aiming to share successful experiences and insights to build a robust AI ecosystem in China [47][48]

Core Insights - The 8th World Artificial Intelligence Conference (WAIC 2025) commenced in Shanghai, with Schneider Electric showcasing its leadership in industrial technology under the theme "Intelligent Connection and Collaborative Influence" [1][2] - Schneider Electric emphasizes the deep integration of AI technology into industrial scenarios, driving digital and green transformation across various sectors in China [2][12] Group 1: AI Applications and Innovations - Schneider Electric has been a pioneer in AI applications for over 20 years, focusing on machine learning and AI algorithms tailored for energy management and industrial automation [3] - The company presented two "Lighthouse Factories" at WAIC, demonstrating significant AI application results: the Shanghai Putuo factory achieved an 82% increase in per capita production efficiency, while the Wuxi factory reduced carbon emissions by 90% through AI-driven ecological design [4][12] - The integration of edge intelligence, large models, and Agentic AI is accelerating penetration into specific industries, creating greater value through the deep fusion of industry-specific knowledge and AI technology [5] Group 2: Product Launches and Solutions - Schneider Electric launched the EcoStruxure Edge Intelligence Box, enhancing data collection, management, real-time computation, and intelligent decision-making capabilities in industrial automation and energy management [7] - The EcoStruxure Open Automation Platform (EAE) was showcased, featuring advanced AI algorithms that optimize the control of multiple motors, highlighting the potential for efficiency and quality improvements in complex industrial production lines [8] - The EcoStruxure Building GPT was introduced as an AI agent for smart building operations, integrating knowledge graphs with large language models to enhance HVAC operations and energy efficiency [9] - A new generation of the EcoStruxure Energy Operation system was tailored for the Chinese market, covering low and medium voltage distribution, microgrid monitoring, and comprehensive energy management [10] - The SmartCool 2.0 solution for data centers utilizes advanced machine learning to optimize cooling output based on IT load demands, significantly reducing energy consumption [11] Group 3: Strategic Collaborations and Research - Schneider Electric's collaboration with various partners aims to enhance AI applications in key industries, focusing on packaging, oil and gas, data centers, smart buildings, and future power grids [6][19] - The company released a report on the energy challenges faced by data centers, proposing a "computing and electricity collaboration" framework to optimize power supply and management [14] - Schneider Electric continues to explore AI's role in driving efficiency and sustainability across critical sectors, reinforcing its commitment to innovation and collaboration in the AI landscape [17][19]