CNS: Core: Small: Energy and Load Management in Data Centers: Online Optimization and Learning

CNS：核心：小型：数据中心的能源和负载管理：在线优化和学习

基本信息

批准号：
1908298
负责人：
Mohammadhassan Hajiesmaili
金额：
$ 49.91万
依托单位：
University of Massachusetts Amherst
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908298&HistoricalAwards=false
关键词：
CNS Core Small Energy Load

项目摘要

Data centers, the backbone of the internet, are using increasingly massive amounts of power, consuming by some estimates up to 3% of the world's power supply and doubling their appetite every four years. This increasing appetite for power has significant ramifications for both costs -- electricity counts among the largest expenses in operating a data center -- and unwelcome contributions to climate change. Major data centers are working to meet this challenge by creating their own renewable energy sources (such as wind and solar farms) and energy storage systems in addition to the electric grid. But the fluctuation and lack of reliability built into the supply of energy from renewable sources causes significant challenges for data centers attempting to efficiently procure energy from these sources in combination with the grid. This project aims to use proven methods of algorithms and machine learning to optimize the energy procurement and load management of data centers under these challenges. In doing so, it will enable data centers to minimize their energy costs, maximize robustness against uncertainty, and improve their energy footprints. As a result, the successful implementation of this project will have a significant impact on lowering the overall cost of internet services. More broadly, by modeling how to more efficiently use renewable sources and energy storage systems, this research has significance beyond data centers. This project will facilitate the efficient and reliable incorporation of renewables into the operations of other large energy customers, playing a key role in moving toward a greener and more sustainable electric grid. The project will broaden participation by involving undergraduates in the research and will include outreach activities on introducing data centers to local K-12 students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数据中心作为互联网的支柱，正在使用越来越大量的电力，据估计消耗了全球电力供应的 3%，并且每四年就会翻一番。对电力日益增长的需求对成本（电力是数据中心运营中最大的开支之一）和对气候变化的不受欢迎的影响都产生了重大影响。除了电网之外，主要数据中心正在努力通过创建自己的可再生能源（例如风能和太阳能发电厂）和储能系统来应对这一挑战。但是，可再生能源供应的波动性和可靠性的缺乏给试图结合电网从这些能源中有效获取能源的数据中心带来了重大挑战。该项目旨在利用经过验证的算法和机器学习方法来优化这些挑战下数据中心的能源采购和负载管理。这样做将使数据中心能够最大限度地降低能源成本，最大限度地提高应对不确定性的鲁棒性，并改善能源足迹。因此，该项目的成功实施将对降低互联网服务总体成本产生重大影响。更广泛地说，通过建模如何更有效地使用可再生能源和能源存储系统，这项研究的意义超出了数据中心的范围。该项目将促进可再生能源高效、可靠地融入其他大型能源客户的运营，在迈向更绿色、更可持续的电网方面发挥关键作用。该项目将通过让本科生参与研究来扩大参与范围，并将包括向当地 K-12 学生介绍数据中心的外展活动。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响进行评估，被认为值得支持审查标准。

项目成果

期刊论文数量（21）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Hierarchical Learning Algorithms for Multi-scale Expert Problems

多尺度专家问题的分层学习算法

DOI：
10.1145/3489048.3530967
发表时间：
2022-06
期刊：
SIGMETRICS/PERFORMANCE '22: Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems
影响因子：
0
作者：
Yang, Lin;Chen, Yu;Hajiesmaili, Mohammad H.;Herbster, Mark;Towsley, Don
通讯作者：
Towsley, Don

Data-driven Competitive Algorithms for Online Knapsack and Set Cover

数据驱动的在线背包和布景竞争算法

DOI：
10.1609/aaai.v35i12.17294
发表时间：
2020-12-09
期刊：
ArXiv
影响因子：
0
作者：
Ali Zeynali;Bo Sun;M. Hajiesmaili;A. Wierman
通讯作者：
A. Wierman

Competitive Bidding Strategies for Online Linear Optimization with Inventory Management Constraints

库存管理约束下的在线线性优化的竞争性投标策略

DOI：
10.1145/3529113.3529115
发表时间：
2022-03
期刊：
ACM SIGMETRICS Performance Evaluation Review
影响因子：
0
作者：
Lee, Russell;Zhou, Yutao;Yang, Lin;Hajiesmaili, Mohammad;Sitaraman, Ramesh
通讯作者：
Sitaraman, Ramesh

Competitive Algorithms for Online Multidimensional Knapsack Problems

在线多维背包问题的竞争算法

DOI：
10.1145/3489048.3522627
发表时间：
2022-06
期刊：
SIGMETRICS/PERFORMANCE '22: Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems
影响因子：
0
作者：
Yang, Lin;Zeynali, Ali;Hajiesmaili, Mohammad H.;Sitaraman, Ramesh K.;Towsley, Don
通讯作者：
Towsley, Don

Emission-aware Energy Storage Scheduling for a Greener Grid

排放感知型储能调度，打造绿色电网

DOI：
10.1145/3396851.3397755
发表时间：
2020-06
期刊：
Eleventh ACM International Conference on Future Energy Systems
影响因子：
0
作者：
Jha, Rishikesh;Lee, Stephen;Iyengar, Srinivasan;Hajiesmaili, Mohammad H.;Irwin, David;Shenoy, Prashant
通讯作者：
Shenoy, Prashant