2024-05-22-NISA-2023年能源人工智能报告_70页_1mb

AI for Energy：利用人工智能加速美国能源转型

这份报告概述了美国能源部国家实验室关于人工智能（AI）在能源领域应用的冬季2023次工作坊成果，重点探讨了AI在核能、电网、碳管理、能源储存和能源材料五大关键领域的潜力与挑战。报告的核心结论如下：

核心理念：

• AI能处理大规模系统、结合数据和物理模型、跨越学科界限，为解决能源领域的人高后果、紧急性和复杂性提供了新机遇。
• 实现拜登政府2035年100%清洁能源电网和2050年净零排放目标，需要将AI置于能源政策和投资的中心位置。

关键领域与机遇：

1. 核能：

   • 挑战： 核电站设计、许可（耗时且昂贵）、部署、运营；
     挑战： 未来看待和自主操作的独特生命安全考量。
   • AI机遇： 快速设计审查、风险知情监管、预测性维护、自主运行副驾驶、加速物理模拟、运营洞察、控制优化。
   • 需AI进展： 能源专属领导力计算生态系统、构建公共基础模型、物理信息模型融合、人员培训、测试床建立、数据获取与共享、公私合作。

2. 电网：

   • 挑战： 管理分布式、可变、多所有权的能源系统；确保网络安全和极端事件下的韧性。
   • AI机遇： 提供主动实时能量系统运营（预见性控制、预测调度）；构建弹性和安全的能源系统；设计100%清洁能源电网。
   • 需AI进展： 多尺度模型与模拟、可解释AI、自动化系统设计、数据聚合与共享、训练数据可用性、多样化联盟、模型信任与安全。

3. 碳管理：

   • 挑战： 加速碳封存、部署、监测与缓解；解决遗留设施排放；预测困难减排领域排放。
   • AI机遇： 虚拟行星孪生（整合能源、环境、社会系统）；打造虚拟地球模型；加速新材料/技术成熟。
   • 需AI进展： 地下物理过程理解、海量多模态AI、知识图谱、先进计算、数据融合、风险建模、可信预言。

4. 能源储存：

   • 挑战： 加速技术开发与部署；优化运营效率；实现公平可及性。
   • AI机遇： 优化子午线/部署/循环；提高储能效率与寿命；响应电网需求。
   • 需AI进展： 领域专用模型、联邦化少拍模型训练、边缘AI控制、解释性AI、计算能力扩展、验证框架。

5. 能源材料：

   • 挑战： 加速从设计到制造；满足清洁能源特定需求（如零碳燃料）。
   • AI机遇： 精准材料设计、制造过程优化、闭环材料使用。
   • 需AI进展： 大规模AI模型训练、物理信息AI、可制造性控制、可解释AI、模块化计算。

共同需AI进展：

• 能源专属领导力计算能力生态系统： 为AI模型培训、托管和基础模型提供国家级平台。
• 能源专属基础模型构建： 开发能理解并组织工程和科学知识的公共AI模型。
• 与物理科学的融合： 将物理知识整合到AI模型中，提高物理合理性。
• 数据聚合、验证和可及性： 建立统一的数据基础设施，解决共享障碍。
• 测试床开发： 提供环境验证AI性能、促进验证方法标准化的平台。
• 领导力人材库建设： 通过强化培训、路径细化活动、跨机构合作等方式，培养具备AI与能源专业知识的人员。

风险管理与政策： 确保AI系统的可靠性、公平性、安全性，遵守监管要求，并考虑对就业的影响。

总体目标： 到2030年，通过AI技术，在这些关键能源领域实现变革性进展，有力支持美国的清洁能源转型。

Summary of Federal Strategic Plan: Artificial Intelligence for the American Prosperity

This document outlines strategic considerations for the U.S. Federal Government regarding Artificial Intelligence (AI) to enhance national prosperity. It views AI as a transformative technology applicable across multiple departments and agencies, including DoD, DOI, DOE, DOT, DOL, DHS, VA, Treasury, State, USAID, and NARA.

Vision:
Leverage AI as an engine for positive change to improve government, the economy, national security, and security for citizens.

Cross-Cutting Priorities:

1. AI Safety, Trustworthiness, and Reliability:

   • Develop principles and frameworks for trustworthy and safe AI, including verifiable robustness and alignment with American values.
   • Advance AI Risk Management Framework development. Foster AI V&V disciplines.

2. AI-Driven Opportunities:

   • Leverage AI for economic growth, including increasing labor productivity, enhancing worker capabilities, fostering entrepreneurship, and boosting long-term U.S. competitiveness.
   • Pioneering AI for national security, including defense, homeland security, intelligence community, and cybersecurity threats stemming from advanced foreign competitors.
   • Leverage AI for scientific discovery and exploring historic applications, including unique scientific and economic opportunities in Earth science, power systems, health, agriculture, climate modeling, and materials science.
   • Promote energy independence by leveraging AI to successfully implement the Energy Renaissance.

3. Industrial AI Maturity:

   • Lead in critical industrial AI maturation including manufacturing and supply chain resiliency.
   • Advance ethical artificial intelligence deployment in the public sector.

4. Private Sector Collaboration:

   • Support AI growth through robust public-private partnerships and removing unnecessary barriers. Promote equity, inclusion, and a diverse workforce in AI.

Cross-Cutting Challenges/Opportunities:

• Talent: Focusing on workforce development, upskilling, and attracting, supporting, and retaining talent.
• Data: Enhancing responsible data access and development consistent with Section 1331 authority.
• Compute: Ensuring the U.S. maintains its leadership in computing for AI.
• Integrity: Addressing disinformation and deepfakes through AI.
• Civil Liberties and Equity: Promoting AI principles ensuring government respects civil liberties and human rights in its use of AI.

Strategic Initiatives: Detail specific actions under each priority area, emphasizing V&V, ethical AI development, public-private partnerships, and addressing workforce, data, and compute challenges.

Five Guiding Principles: AI safety/trustworthiness, AI-driven public sector transformation, industrial AI leadership, governmental AI excellence, equity and access, civil liberties, and robustness/alignment.

Conclusion: AI presents America with a significant opportunity to meet pressing challenges and leverage unique strengths. These recommendations provide a blueprint for developing responsible policies and strategies that can fundamentally enhance American innovation, prosperity, and global competitiveness through the judicious use of Artificial Intelligence.
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