2025能源与人工智能报告 ( 英文 304 页)

目录

前言 ..... 3

致谢 ..... 5

执行摘要 ....... 13

第1章：人工智能的崛起及其与能源的关系

1.1 引言 ....... 20

1.2 人工智能的崛起 ...... 21

1.2.1 金融市场中的高涨预期 ..... 22

1.2.2 家庭和企业如何使用人工智能？ ..... 24

1.3 什么是人工智能？ ..... 28

1.3.1 人工智能的类型 ..... 29

1.3.2 人工智能供应链 .... 30

1.3.3 人工智能基础设施的类型 ...... 32

1.3.4 人工智能的能力及其衡量方式 .... 34

1.4 人工智能的能源需求与能源领域的人工智能应用 ..... 37

1.4.1 人工智能模型的生命周期与能源消耗 ..... 39

第2章：人工智能的能源需求

2.1 引言 ....... 50

2.1.1 案例设计 .... 50

2.1.2 关键定义与概念 ..... 51

2.2 数据中心的电力消耗 .... 54

2.2.1 数据中心的历史电力消耗 .... 54

2.3 数据中心电力消耗的前景展望 .... 62

2.3.1 基准情景下的展望 ....... 62

2.3.2 敏感性情景下的展望 ..... 66

2.4 人工智能对ICT行业能源使用的影响 ...... 71

2.4.1 边缘人工智能应用的驱动因素与前景 .... 72

2.5 满足数据中心需求的电力供应 .... 75

2.5.1 科技公司的采购策略 .... 75

2.5.2 电力供应与数据中心需求的匹配 ...... 79

2.5.3 基准情景下的电力供应 ..... 86

2.5.4 敏感性情景下的电力供应 ....... 91

2.6 数据中心与电网的互动 ...... 93

2.6.1 数据中心接入电网是否存在延迟风险？ ....... 93

2.6.2 数据中心的地理灵活性 .... 96

2.6.3 数据中心的运营灵活性 ....... 100

2.6.4 优化与电力系统运营商和规划者的互动 ....... 105

第3章：人工智能优化能源系统

3.1 引言 ..... 110

3.2 人工智能在能源系统中的作用 ..... 112

3.3 人工智能在能源与矿产供应中的应用 ....... 114

3.3.1 人工智能在石油和天然气供应中的应用 ....... 115

3.3.2 人工智能在关键矿产供应中的应用 ...... 120

3.4 人工智能在电力行业的应用 ...... 122

3.4.1 电力系统运营中的人工智能应用 ...... 122

3.4.2 发电厂与储能中的人工智能应用 ...... 124

3.4.3 人工智能在电网中的应用 ....... 129

3.5 人工智能在终端能源消费中的应用 ..... 134

3.5.1 工业中的人工智能 ...... 134

3.5.2 交通中的人工智能 .... 143

3.5.3 建筑中的人工智能 ..... 150

3.6 人工智能提升能源系统韧性 ....... 159

3.7 人工智能在能源优化中应用的障碍 ....... 162

第4章：人工智能推动能源创新

4.1 引言 ..... 166

4.2 从专利和初创企业中学到什么？ ..... 168

4.3 人工智能如何加速能源创新挑战的解决？.... 172

4.3.1 创新周期概述 .... 172

4.3.2 将人工智能融入创新流程 ...... 173

4.3.3 哪些能源技术领域将受益于人工智能？ ...... 175

4.4 聚焦四个关键技术领域 .... 177

4.4.1 电池 ...... 177

4.4.2 合成燃料生产催化剂 .... 181

4.4.3 二氧化碳捕集材料 ...... 185

4.4.4 水泥生产 ...... 190

4.4.5 总结 ...... 194

4.5 加速人工智能创新的政策 .... 198

4.5.1 创新资金 ...... 198

4.5.2 数据、模型与计算基础设施 ....... 200

4.5.3 结论与未来方向 ....... 203

第5章：能源与人工智能的新兴议题

5.1 引言 ..... 206

5.2 人工智能时代的能源安全 ....... 207

5.2.1 提升能源安全的人工智能应用 ..... 207

5.2.2 人工智能能源供应链的安全性 ...... 209

5.2.3 智能整合数据中心以降低风险 ..... 215

5.3 加强技术行业与能源行业的对话 .... 217

5.3.1 更好地理解需求前景 ....... 217

5.3.2 释放数字行业的创新潜力 ....... 219

5.4 投资影响..... 222

5.4.1 数据中心投资 ....... 222

5.4.2 数据中心支持电力投资的潜力 ...... 226

5.5 能源行业的数字技能是否成为瓶颈？ .... 229

5.5.1 能源行业对人工智能和数字技能的需求 ...... 229

5.5.2 能源企业提升人工智能素养的障碍 ....... 231

5.6 弥合数字鸿沟：新兴市场和发展中经济体的能源与人工智能关系 ..... 233

5.6.1 电力可靠性作为新兴市场和发展中经济体的障碍 ....... 234

5.6.2 人工智能在能源领域的应用在新兴市场和发展中经济体的作用 ..... 235

5.6.3 克服多样化障碍并为包容性人工智能奠定政策基础 ..... 237

5.7 人工智能与能源政策格局 .... 238

5.7.1 政府在人工智能发展中的推动作用 ...... 238

5.7.2 能源与人工智能政策框架 .... 240

5.8 探索人工智能对排放的潜在影响 ..... 244

5.8.1 数据中心排放增长的背景分析 ..... 246

5.8.2 人工智能在减少能源使用排放中的作用 ..... 249

5.8.3 人工智能反弹效应的不确定性 ...... 251

附录

附录A. 方法与数据表 ...... 255

附录B. 定义 .... 261

附录C. 参考文献 ....... 275

Table of Contents

Foreword ..... 3

Acknowledgements ..... 5

Executive Summary ....... 13

Chapter 1: The Rise of AI and Its Nexus with Energy

1.1 Introduction ....... 20

1.2 The Rise of AI ...... 21

1.2.1 Surging Expectations in Financial Markets ..... 22

1.2.2 How Do Households and Businesses Use AI? ..... 24

1.3 What Is AI? ..... 28

1.3.1 Types of AI ..... 29

1.3.2 The AI Supply Chain .... 30

1.3.3 Types of AI Infrastructure ...... 32

1.3.4 How Capable Is AI and Can We Measure It?.... 34

1.4 Energy for AI and AI for Energy ..... 37

1.4.1 AI Model Life Cycle and Energy Consumption ..... 39

Chapter 2: Energy for AI

2.1 Introduction ....... 50

2.1.1 Case Design .... 50

2.1.2 Key Definitions and Concepts ..... 51

2.2 Electricity Consumption of Data Centres .... 54

2.2.1 Historical Electricity Consumption of Data Centres .... 54

2.3 Outlook for Electricity Consumption from Data Centres .... 62

2.3.1 Outlook in the Base Case ....... 62

2.3.2 Outlook in the Sensitivity Cases ..... 66

2.4 Implications of AI for ICT Sector Energy Use ...... 71

2.4.1 Drivers and Outlook for Edge Applications of AI .... 72

2.5 Electricity Supply to Meet Data Centre Demand .... 75

2.5.1 Procurement Strategies of Technology Companies .... 75

2.5.2 Matching Electricity Supply with Data Centre Demand ...... 79

2.5.3 Electricity Supply in the Base Case ..... 86

2.5.4 Electricity Supply in the Sensitivity Cases ....... 91

2.6 Data Centre Interactions with the Electricity Grid ...... 93

2.6.1 Is There a Risk of Delays in Connecting Data Centres to the Grid? ....... 93

2.6.2 Data Centre Locational Flexibility .... 96

2.6.3 Data Centre Operational Flexibility ....... 100

2.6.4 Optimising Interactions with Power System Operators and Planners ....... 105

Chapter 3: AI for Energy Optimisation

3.1 Introduction ..... 110

3.2 The Role of AI in the Energy System ..... 112

3.3 AI for Energy and Minerals Supply ....... 114

3.3.1 AI for Oil and Gas Supply ....... 115

3.3.2 AI for Critical Minerals Supply ...... 120

3.4 AI for the Electricity Sector ...... 122

3.4.1 AI Applications for Power System Operations ...... 122

3.4.2 AI Applications for Power Plants and Storage ...... 124

3.4.3 AI for Electricity Networks ....... 129

3.5 AI for Energy End Uses ..... 134

3.5.1 AI for Industry ...... 134

3.5.2 AI for Transport .... 143

3.5.3 AI for Buildings ..... 150

3.6 AI for Energy System Resilience ....... 159

3.7 Barriers to the Adoption of AI for Energy Optimisation ....... 162

Chapter 4: AI for Energy Innovation

4.1 Introduction ..... 166

4.2 What Can We Learn from Patents and Start-ups? ..... 168

4.3 How Can AI Accelerate Solutions to Energy Innovation Challenges?.... 172

4.3.1 Overview of the Innovation Cycle .... 172

4.3.2 Integrating AI into the Innovation Process ...... 173

4.3.3 What Energy Technology Areas Will Be Accelerated by AI? ...... 175

4.4 Focus on Four Selected Technology Areas .... 177

4.4.1 Batteries ...... 177

4.4.2 Catalysts for Synthetic Fuel Production .... 181

4.4.3 CO₂ Capture Materials ...... 185

4.4.4 Cement Production ...... 190

4.4.5 Summary ...... 194

4.5 Policies to Accelerate AI Innovation .... 198

4.5.1 Innovation Funding ...... 198

4.5.2 Data, Models and Computing Infrastructure ....... 200

4.5.3 Conclusions and Future Directions ....... 203

Chapter 5: Emerging Themes on Energy and AI

5.1 Introduction ..... 206

5.2 Energy Security in the Age of AI ....... 207

5.2.1 Applications of AI That Enhance Energy Security ..... 207

5.2.2 The Security of Energy Sector Supply Chains for AI ...... 209

5.2.3 Smart Integration of Data Centres to Mitigate Risks ..... 215

5.3 Enhancing the Dialogue Between the Technology Sector and the Energy Industry .... 217

5.3.1 Better Understanding the Outlook for Demand ....... 217

5.3.2 Leveraging the Innovation Potential of the Digital Sector ....... 219

5.4 Implications for Investment..... 222

5.4.1 Data Centre Investment ....... 222

5.4.2 Potential for Data Centres to Support Electricity Investment ...... 226

5.5 Are Digital Skills in the Energy Sector a Bottleneck? .... 229

5.5.1 Demand for AI and Digital Skills in the Energy Sector ...... 229

5.5.2 Barriers to Developing AI Literacy in Energy Firms ....... 231

5.6 Bridging the Digital Divide: The Energy-AI Nexus in Emerging Market and Developing Economies ..... 233

5.6.1 Power Reliability as a Barrier in Emerging Market and Developing Economies ....... 234

5.6.2 The Role of AI Applications in the Energy Sector in Emerging Market and Developing Economies ..... 235

5.6.3 Overcoming Diverse Barriers and Laying the Policy Groundwork for Inclusive AI in Energy ..... 237

5.7 The AI and Energy Policy Landscape .... 238

5.7.1 The Enabling Role of Government in AI Development ...... 238

5.7.2 Energy and AI Policy Frameworks .... 240

5.8 An Exploratory Approach to Determine the Potential Impact of AI on Emissions ..... 244

5.8.1 Contextualising Emissions Growth from Data Centres ..... 246

5.8.2 The Role of AI in Reducing Emissions from Energy Use ..... 249

5.8.3 The Uncertain Impacts of Rebound Effects from AI ...... 251

Annexes

Annex A. Methodology and Data Tables ...... 255

Annex B. Definitions .... 261

Annex C. References ....... 275

×