CaltechAUTHORS
  A Caltech Library Service

Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation

Liu, Zhenhua and Wierman, Adam and Cheng, Yuan and Razon, Benjamin and Chen, Niangjun (2013) Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation. In: SIGMETRICS '13 Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. ACM , New York, NY, pp. 341-342. ISBN 978-1-4503-1900-3. https://resolver.caltech.edu/CaltechAUTHORS:20130904-124117730

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20130904-124117730

Abstract

Demand response is a crucial aspect of the future smart grid. It has the potential to provide significant peak demand reduction and to ease the incorporation of renewable energy into the grid. Data centers’ participation in demand response is becoming increasingly important given the high and increasing energy consumption and the flexibility in demand management in data centers compared to conventional industrial facilities. In this extended abstract we briefly describe recent work in [1] on two demand response schemes to reduce a data center’s peak loads and energy expenditure: workload shifting and the use of local power generations. In [1], we conduct a detailed characterization study of coincident peak data over two decades from Fort Collins Utilities, Colorado and then develop two algorithms for data centers by combining workload scheduling and local power generation to avoid the coincident peak and reduce the energy expenditure. The first algorithm optimizes the expected cost and the second one provides a good worst-case guarantee for any coincident peak pattern. We evaluate these algorithms via numerical simulations based on real world traces from production systems. The results show that using workload shifting in combination with local generation can provide significant cost savings (up to 40% in the Fort Collins Utilities’ case) compared to either alone.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/2465529.2465740DOIArticle
ORCID:
AuthorORCID
Chen, Niangjun0000-0002-2289-9737
Additional Information:Copyright is held by the author/owner(s). This work was supported by NSF grants CNS 0846025, DoE grant DE-EE0002890, and HP Labs.
Funders:
Funding AgencyGrant Number
NSFCNS-0846025
Department of Energy (DOE)DE-EE0002890
HP LabsUNSPECIFIED
Subject Keywords:Demand response, coincident peak pricing, data center, work- load shifting, online algorithm
Classification Code:C.0 [Computer Systems Organization]: General
DOI:10.1145/2465529.2465740
Record Number:CaltechAUTHORS:20130904-124117730
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20130904-124117730
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:41084
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:04 Sep 2013 20:02
Last Modified:10 Nov 2021 04:25

Repository Staff Only: item control page