Core Insights - The integration of energy and AI represents a deep fusion of the real economy and digital technology, driven by policies aimed at enhancing efficiency and controlling carbon emissions [1][4] - The concept of a "closed-loop" system in energy digitalization is essential for creating incremental value, emphasizing the importance of perception, cognition, and decision-making [2][3] - The energy sector is undergoing a transformation towards digitalization, with New Hope Energy's initiatives leading to significant energy savings and carbon reduction [3][5] Energy and AI Integration - The development of "Energy + AI" is characterized by a closed-loop system that enables intelligent decision-making, which is crucial for adding value to clients [2][3] - New Hope Energy has implemented a comprehensive energy system that integrates various energy sources, aiming to provide deep energy and carbon digital services to over 9,500 enterprises and 200 parks by 2025 [3] Challenges and Future Outlook - The current stage of "Energy + AI" is likened to a youthful phase, with various factors influencing its maturity, including policy guidance and industry recognition [4][6] - The energy sector faces challenges in adopting AI due to the complexity and real-time nature of industry data, necessitating a shift from single-point product optimization to comprehensive energy solutions [5] - The future of energy digital services will depend on the ability to create standardized solutions and modules that can be adapted to different industry needs, fostering a platform for innovation [5][6]

近日在美关税如过山车般"反复横跳"之下，部分出口型企业大受影响，订单量在"观望停滞"与"集中释 放"之间剧烈震荡，让企业生产线经历着"停摆"与"赶工"的极端切换——前期因关税不确定性导致美国 订单锐减，车间设备一度沉寂；随着阶段性政策窗口开启，积压订单快速回流，企业不得不开足马力、 昼夜赶工，这种"冰火两重天"的生产节奏，对供应链的韧性提出了极限挑战。 作为制造业生产链条的重要环节之一，能源供能行业在这种高度的不确定环境中受到了极大的考验。多 位天然气行业一线人士对记者表示，其经手的多宗天然气订单受影响，短期出现"取消—恢复"等不稳定 现象，对于企业日常运营带来了较大的冲击。 面对这场"关税海啸"带来的不确定性，中国天然气企业不再仅靠被动防守，而是通过"多元稳供、跨链 服务、数智赋能"等措施主动求变。中国能源头部企业新奥股份表示传统模式不能及时、有效满足客户 变化，必须用智能实现供需最优匹配，帮助客户降低用气成本。 中国企业未雨绸缪式地投身于行业的迭代升级中，以求在未来的能源转型中占据主动，同时也为中国生 产企业的降本增效作出自己的一份贡献。 多元稳供：从"保供"到"灵活供应"的升级 在全球能源市场呈现动荡态 ...

Core Viewpoint - Natural gas is increasingly recognized as a long-term energy source rather than merely a transitional one, with its flexible integration with renewable energy sources like wind and solar being emphasized at the 29th World Gas Conference (WGC2025) [1][2]. Industry Insights - The current share of natural gas in China's primary energy consumption is only 8.5%, significantly lower than the global average of 24%, indicating substantial future growth potential [3]. - China's apparent natural gas consumption is projected to reach 426 billion cubic meters in 2024, with an annual growth rate of 8% [3]. - By 2030, China's total natural gas consumption is expected to reach between 550 billion and 600 billion cubic meters, driven by the need for cleaner energy and the growth of LNG demand in the transportation sector [3][6]. Company Developments - New Energy's gas sales are expected to approach 40 billion cubic meters in 2024, with industrial and commercial gas usage growing by over 5% year-on-year [4]. - New Energy has launched a natural gas capability recognition model through its platform, "Good Gas Network," to optimize supply and demand matching, significantly reducing costs for customers and increasing profits for city gas companies [7][8]. Technological Innovations - The integration of AI, blockchain, big data, and other advanced technologies is transforming the energy system, moving from experience-based management to data-driven intelligence [7][9]. - New Energy has deployed over 130,000 IoT sensing devices and 20,000 visualization devices across various scenarios, establishing a comprehensive smart safety management system [10]. Future Outlook - The company anticipates a growth trajectory for natural gas over the next 10 to 15 years, with an expected annual growth rate of around 5% [6]. - The development of comprehensive energy services driven by AI is seen as essential for creating value for customers and enhancing operational efficiency [11].