Data center and load aggregator coordination towards electricity demand response

IF 3.8 3区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Sustainable Computing-Informatics & Systems Pub Date : 2024-01-14 DOI:10.1016/j.suscom.2024.100957
Yijia Zhang , Athanasios Tsiligkaridis , Ioannis Ch. Paschalidis , Ayse K. Coskun
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Abstract

In a demand response scenario, coordinating multiple data centers with an electricity load aggregator provides opportunities to minimize electricity cost and absorb the volatility in the grid that is caused by renewable generation. To enable optimal coordination, this paper introduces a joint data center and aggregator optimization framework that minimizes the cost of data centers while they participate in demand response programs regulated by a load aggregator. The proposed framework, DCAopt, solves three integrated optimization problems: optimizing the quality-of-service of jobs in each data center, coordinating workload sharing among multiple data centers, and assigning (electricity) prices that incentivize demand response. Instead of relying on simplified relations between a data center’s overall utilization rate and the average job delay, DCAopt applies queueing theory and job scheduling simulation techniques to model data centers with heterogeneous workloads, where different workload properties can be measured using data from actual servers. DCAopt solves the aforementioned joint optimization problems via gradient descent. Through evaluation using fine-grained simulations, we demonstrate that our framework finds better solutions to the data-center-aggregator optimization problems. With DCAopt, the energy costs of data centers can be reduced by 5% on average, with a corresponding reduction of a social cost assessed by the aggregator amounting to more than 30% in most cases. In addition, power usage reduction at the data centers is 6% higher compared to data-center-centric power use optimization.

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数据中心与负荷聚合器协调实现电力需求响应
在需求响应方案中,将多个数据中心与电力负荷聚合器协调起来,可以最大限度地降低电力成本,并吸收可再生能源发电造成的电网波动。为实现最佳协调,本文介绍了一个数据中心与聚合器联合优化框架,该框架可在数据中心参与由负载聚合器监管的需求响应计划时,最大限度地降低数据中心的成本。所提出的 DCAopt 框架解决了三个综合优化问题:优化每个数据中心的工作服务质量、协调多个数据中心之间的工作量共享,以及分配激励需求响应的(电力)价格。DCAopt 不依赖于数据中心总体利用率和平均作业延迟之间的简化关系,而是应用排队理论和作业调度模拟技术,为具有异构工作负载的数据中心建模,其中不同的工作负载属性可通过实际服务器的数据进行测量。DCAopt 通过梯度下降法解决上述联合优化问题。通过使用细粒度模拟进行评估,我们证明了我们的框架能为数据中心-聚合器优化问题找到更好的解决方案。利用 DCAopt,数据中心的能源成本平均可降低 5%,在大多数情况下,聚合器评估的社会成本可相应降低 30% 以上。此外,与以数据中心为中心的用电优化相比,数据中心的用电量减少了 6%。
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来源期刊
Sustainable Computing-Informatics & Systems
Sustainable Computing-Informatics & Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTUREC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
10.70
自引率
4.40%
发文量
142
期刊介绍: Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.
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