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引用次数: 0
摘要
在社会不断数字化、数据量呈指数级增长、能源需求日益增长的时代,能源管理在数据中心(DC)中发挥着不可或缺的作用,也是实现去碳化的关键因素。鉴于数据中心的复杂性,传统的能源管理策略是不够的。本研究以 OODA(观察、定位、决策和行动)循环为基础,根据爱立信在瑞典林雪平运营的数据中心的经验,为数据中心引入了一个数据驱动的决策框架。所开发的框架使配送中心能够有效提高能源效率。该框架以 OODA 循环为基础,利用来自 DC 建筑管理系统的大量数据集,通过数据驱动的战略决策,帮助减少制冷能耗。通过采用人工智能方法,特别是本研究中的 K-means 聚类,对 PID(比例、积分、微分)参数进行持续监控和微调,该框架有助于提高运行效率。
Next-generation data center energy management: a data-driven decision-making framework
In the era of society’s ongoing digitization and the exponential growth in data volume, alongside a growing energy demand, energy management plays an integral role in data centers (DCs) and is a key factor in the quest for decarbonization. In light of the complex nature of DCs, traditional energy management strategies are inadequate. This research introduces a data-driven decision-making framework for DCs, grounded in the OODA (Observation, Orientation, Decision, and Action) loop and based on insights from an Ericsson-operated DC in Linköping, Sweden. The developed framework enables DCs to enhance energy efficiency effectively. Rooted in the OODA loop and leveraging extensive datasets from DCs’ building management systems, this framework aids in decreasing cooling energy usage through strategic, data-driven decision-making. By adopting AI methods, specifically K-means clustering in this research, for continuous monitoring and fine-tuning (Proportional, Integral, Derivative) PID parameters, the framework aids in improving operational efficiency.
期刊介绍:
Frontiers in Energy Research makes use of the unique Frontiers platform for open-access publishing and research networking for scientists, which provides an equal opportunity to seek, share and create knowledge. The mission of Frontiers is to place publishing back in the hands of working scientists and to promote an interactive, fair, and efficient review process. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria