文 | 远景储能 日前，全球领先的绿色科技企业远景科技集团（下称 " 远景 " ）宣布与英国能源企业 Statera Energy 达成战略合作，将为英国 Carrington 储能项目提供系统级解决方案。该 项目总装机容量达 680MW/1360MWh ，是英国单体容量最大的储能项目之一。 项目建 成后，不仅能为约 220 万户家庭持续供电 2 小时，还能减少弃风弃光、有效提升电网稳定 性，助力英国实现净零排放与能源安全目标。 除了在储能系统集成领域的全球经验，远景在物理人工智能、 AI 驱动可再生能源解决方案 等方面的开创性优势是 Statera 选择远景的重要依据。 英国被业内视为全球最典型的"交易型储能"市场之一。依托成熟的电力交易机制，其储能 市场高度市场化，储能资产可以参与电力中长期、现货、容量市场以及辅助服务领域多个品 种的交易。如何在收益多元化的同时保障收益的稳定性，成为英国储能市场的重要课题。 据介绍，远景将为 Carrington 储能项目提供能源大模型驱动的智慧储能系统。 该系统专 为高比例可再生能源并网场景设计，具备高能量密度、低噪音、高灵活度和高收益等优势。 依托"远景天枢"能源大模 ...

Core Viewpoint - The article discusses the successful implementation of the world's largest AI-powered independent power system at the Yuanjing Chifeng Green Hydrogen and Ammonia Project, demonstrating the feasibility of a 100% green electricity direct connection for industrial applications [2][4]. Group 1: Project Overview - The Yuanjing Chifeng Green Hydrogen and Ammonia Project is recognized as the largest green hydrogen and ammonia project globally, achieving 100% green electricity direct connection and operating stably for over 22 months [4][6]. - The project utilizes a 2GW-level independent AI power system, marking the first large-scale implementation of a "wind-solar-storage-hydrogen-ammonia" dynamic coupling in industrial settings [4][6]. Group 2: Technological Innovations - The AI power system integrates the "Yuanjing Tianji" meteorological model and the "Yuanjing Tianshu" energy model, enhancing planning, forecasting, scheduling, and operation capabilities with real-time adjustments and self-learning abilities [6][8]. - The system has improved power prediction accuracy by approximately 10% and reduced electricity costs by about 20% through high-precision power forecasting and intelligent scheduling [8]. Group 3: Industry Impact and Replication - The success of the Yuanjing Chifeng project has paved the way for replicating the "Yuanjing solution" in high-energy-consuming industries, with over 150 companies from sectors like steel, chemicals, and non-ferrous metals participating in discussions on green energy solutions [9][11]. - The collaboration with Xiangfu Technology in Inner Mongolia has established a benchmark for green electricity direct connection projects, achieving over 60% green electricity usage and creating a closed-loop green industrial chain [11][12]. Group 4: Environmental Benefits - The project in Baotou, Inner Mongolia, utilizes over 70% renewable energy, significantly reducing energy costs and carbon emissions, saving approximately 15.27 million tons of standard coal and reducing CO2 emissions by about 44.3 million tons annually [12]. - The advancements in green electricity direct connection are positioned as essential for achieving zero-carbon transitions in various industries, aligning with global carbon tariff mechanisms and energy transition initiatives [12].

Core Viewpoint - The energy industry is transitioning from traditional "material assets" to future "AI assets" driven by physical artificial intelligence, which will reshape competition and operational efficiency in the sector [1][5]. Group 1: Future Energy Systems - The future energy system will evolve from simple equipment stacking to an ecosystem of intelligent agents, capable of safely operating while integrating more green electricity to support low-cost, high-quality clean energy for economic development [3][4]. - Artificial intelligence will play a crucial role in constructing future energy systems, moving from being a tool to becoming a central entity that enhances decision-making and operational efficiency [5][10]. Group 2: Market Innovations and Applications - The successful completion of the world's first green ammonia fuel bunkering operation at Dalian Port marks a milestone in global green shipping, showcasing the complete value chain from green electricity to ammonia fuel for shipping [7][9]. - The Chifeng Zero Carbon Hydrogen Energy Industrial Park serves as a training ground for energy models, providing a closed-loop system that generates vast amounts of data and enhances global perception [9][12]. Group 3: AI's Role in Energy Sector - AI is transforming the energy sector by enabling companies to manage market risks and optimize asset value, shifting the focus from mere production to value-based competition [10][12]. - The concept of "physical artificial intelligence" integrates AI with physical laws and knowledge graphs, enhancing the reliability of AI applications in energy systems and addressing challenges faced by traditional AI models [12][13]. Group 4: China's Competitive Advantage - China possesses significant market demand, complex energy systems, a complete industrial chain, and practical capabilities, positioning it to lead in the development of physical artificial intelligence and energy models globally [12].

Core Viewpoint - The wind power industry is at a critical juncture of technological iteration and model innovation, with Envision Energy launching the Galileo AI Wind Turbine, which integrates advanced meteorological and energy models to enhance wind farm revenue by over 20% [1][5][16] Group 1: Industry Challenges - The wind power sector faces dual challenges of "uncertain power generation" and "price volatility," complicating investment return assessments [3][16] - A recent client reported that an investment report for a wind power project could not pass the decision-making committee due to unpredictable revenue [3] Group 2: Technological Innovations - The Galileo AI Wind Turbine combines the "Tianji" meteorological model and the "Tianshu" energy model, utilizing multi-modal data and advanced computational capabilities to provide accurate forecasts for 15-30 days within just three minutes [5][6] - The integration of these models allows for enhanced predictive accuracy and revenue optimization for wind farms, with a reported 20.9% revenue increase for AI-equipped turbines compared to non-AI counterparts [5][6] Group 3: Reliability and Quality - The wind power industry has experienced rapid growth driven by larger turbines, but this has also amplified reliability issues [8][10] - Envision Energy emphasizes the importance of "technical accumulation" and "in-house manufacturing" to ensure high reliability and performance, addressing the industry's fragmented approach to technology [10][11] - The company has developed a comprehensive reliability management system that identifies weak points in the turbine's components and connections, enhancing overall system reliability [10][11] Group 4: Strategic Transition - The wind power sector is transitioning from being merely a "single power generation device" to a core participant in new energy systems, with a focus on "system safety" and "energy certainty" rather than just cost per kilowatt-hour [12][15] - Envision Energy's approach integrates AI and energy solutions, positioning the company to lead the industry towards a more value-driven model rather than mere scale expansion [12][16] Group 5: Market Dynamics - As the energy market becomes more complex, the demand for "certainty" has become paramount for clients, with Envision Energy addressing this through advanced forecasting and intelligent control systems [16] - The company is redefining the role of wind power from a passive energy source to an intelligent entity capable of understanding market dynamics and capturing value [16]