AIDC 自备电源调研 20251211 摘要 美国大缸径柴油发动机产能紧张，主要受限于生产制造能力、测试能力 和关键零部件供应链。博世作为主要燃油系统供应商，因能源转型投资 意愿较弱，加剧了零部件供应瓶颈，且国产替代难度大。 中国数据中心建设增速放缓，受 H20 事件和政策监管影响，2025 年建 设规模或难显著增长。成本敏感性提升，国产替代需求增加，但外资机 组在技术层面仍有优势，需调整商务策略应对。 数据中心备用电源与其功率成线性比例，通常配备 10-40 台柴油发电机， 主力功率段在 1.6-2.4 兆瓦之间。备用电源成本占比约为 25%，成本控 制影响业主对国内外机组的选择。 国产替代面临挑战，高技术含量零部件如博世油泵、电控系统和 ABB 涡 轮增压器难以替代，因技术难度高、缺乏规模效应且投资回报周期长。 基础金属加工件国产化程度较高。 美国数据中心需求旺盛，但本土制造业疲软，次一级零部件难以替换， 康明斯和卡特彼勒扩产意愿不强，通过维持后端需求饥饿状态保持竞争 优势，导致供应链持续紧张。 Q&A 近期美国数据中心业务需求旺盛，导致柴油发动机（柴发）在该领域的出货量 大幅增长。请问目前行业内部的情 ...

Core Insights - The essence of AI competition has shifted to an "electricity competition," with investment trends moving from traditional IT infrastructure to non-IT infrastructure such as power, cooling, and materials [1][6][12] - By 2030, China's non-IT infrastructure investment related to AI is expected to reach 800 billion RMB, with power systems dominating at 38%, followed by metals for data center construction at 12% and advanced cooling systems at 10% [2][9] Investment Trends - The investment wave in AI infrastructure is expanding beyond traditional chips and servers to include essential non-IT infrastructure [2] - Total capital expenditure for AI in China is projected to grow to 2-2.5 trillion RMB by 2030, with non-IT infrastructure accounting for one-third of this total [2] Power Consumption and Data Centers - The energy consumption of data centers in China is expected to grow at a compound annual growth rate (CAGR) of 18%, increasing from 102 TWh in 2024 to 277 TWh by 2030, representing 29% of global data center electricity consumption [3][9] - The rapid increase in power consumption is driven by the accelerated adoption of AI data centers (AIDC), which have significantly higher power requirements than traditional data centers [4] Key Drivers of Investment - The report identifies three main drivers for the surge in investment: the proliferation of AIDC, the deployment of high-performance chips, and the increasing power density of server cabinets [4][5][9] Opportunities in Power Supply - China has significant advantages in AI power infrastructure, including ample generation capacity, lower industrial electricity prices (30-60% lower than developed markets), a leading position in renewable energy supply chains, and a relatively young and robust power grid [12] - Five major investment opportunities are highlighted: nuclear power, electrical equipment, battery energy storage systems (BESS), diesel generators, and advanced power supply technologies [13][17][20][22][24] Cooling and Materials - Efficient cooling and essential raw materials are critical for AI infrastructure, with significant investment potential [25] - Liquid cooling technology is expected to grow rapidly, with a projected market size of 79 billion RMB by 2030, driven by the need for efficient heat management in high-density AI environments [26] - The demand for key metals such as copper and aluminum is also expected to rise, with copper consumption in AI data centers projected to reach approximately 1 million tons by 2030, accounting for 5-6% of national demand [27]