下一代以人工智能为重点的数据中心与智能电网和区域能源系统的集成和交互:最新技术、机遇和挑战

IF 16.3 1区 工程技术 Q1 ENERGY & FUELS
Yingbo Zhang , Hong Tang , Hangxin Li , Shengwei Wang
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引用次数: 0

摘要

人工智能(AI)和高性能计算(HPC)的快速发展大大增加了对数据中心容量的需求,特别是对图形处理单元(GPU)数据中心的需求。这些数据中心提供了增强的计算能力,但它们也比传统数据中心消耗更多的电力。然而,现有的评论主要集中在关于能源方面的通用计算的传统数据中心的作用。本文重新思考了下一代以人工智能为重点的GPU数据中心作为产消者的角色,即能源的生产者和消费者,当与智能电网和区域能源系统集成并交互时。首先,我们系统地回顾了现有的增强智能电网内数据中心能源灵活性的策略和方法,并强调了与传统数据中心相比,GPU数据中心独特的计算工作负载特征和ai驱动的灵活性。其次,我们全面总结了变革性冷却技术,特别是液体冷却,GPU数据中心的高品位废热回收潜力及其各种应用。第三,我们深入讨论了可再生能源整合和弃风的机会和技术,作为GPU数据中心脱碳的关键战略。此外,本研究还详细阐述了GPU数据中心作为产消者在智能电网和区域能源系统中的潜在挑战和未来前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integration and interaction of next-generation AI-focused data centers with smart grids and district energy systems: The state-of-the-art, opportunities and challenges

Integration and interaction of next-generation AI-focused data centers with smart grids and district energy systems: The state-of-the-art, opportunities and challenges
The rapid evolution of artificial intelligence (AI) and high-performance computing (HPC) has significantly increased the demand for data center capacity, particularly for Graphics Processing Unit (GPU) data centers. These data centers offer enhanced computational capabilities, but they also consume significantly more electricity than traditional data centers. However, existing reviews primarily focus on the role of traditional data centers for general-purpose computing concerning energy aspects. This paper rethinks the role of next-generation AI-focused GPU data centers as prosumers-both producers and consumers of energy, when integrated with and interacting within smart grids and district energy systems. First, we systematically review the existing strategies and methods to enhance the energy flexibility of data centers within the smart grids and highlight unique computing workload characteristics and AI-driven flexibility of GPU data centers in comparison with traditional data centers. Second, we comprehensively summarize transformative cooling technologies, particularly liquid cooling, the higher-grade waste heat recovery potential of GPU data centers and their various applications. Third, we thoroughly discuss the opportunities and technologies for renewable energy integration and curtailment as key strategies for GPU data center decarbonizations. Furthermore, this study elaborates on potential challenges and future perspectives of GPU data centers within smart grids and district energy systems as prosumers.
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来源期刊
Renewable and Sustainable Energy Reviews
Renewable and Sustainable Energy Reviews 工程技术-能源与燃料
CiteScore
31.20
自引率
5.70%
发文量
1055
审稿时长
62 days
期刊介绍: The mission of Renewable and Sustainable Energy Reviews is to disseminate the most compelling and pertinent critical insights in renewable and sustainable energy, fostering collaboration among the research community, private sector, and policy and decision makers. The journal aims to exchange challenges, solutions, innovative concepts, and technologies, contributing to sustainable development, the transition to a low-carbon future, and the attainment of emissions targets outlined by the United Nations Framework Convention on Climate Change. Renewable and Sustainable Energy Reviews publishes a diverse range of content, including review papers, original research, case studies, and analyses of new technologies, all featuring a substantial review component such as critique, comparison, or analysis. Introducing a distinctive paper type, Expert Insights, the journal presents commissioned mini-reviews authored by field leaders, addressing topics of significant interest. Case studies undergo consideration only if they showcase the work's applicability to other regions or contribute valuable insights to the broader field of renewable and sustainable energy. Notably, a bibliographic or literature review lacking critical analysis is deemed unsuitable for publication.
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