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Pricing data center demand response

Liu, Zhenhua and Liu, Iris and Low, Steven and Wierman, Adam (2014) Pricing data center demand response. In: SIGMETRICS '14 The 2014 ACM international conference on Measurement and modeling of computer systems. ACM , New York, NY, pp. 111-123. ISBN 978-1-4503-2789-3. http://resolver.caltech.edu/CaltechAUTHORS:20161128-163510694

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Abstract

Demand response is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demand response: data centers. We use simulations to show that, not only are data centers large loads, but they can provide as much (or possibly more) flexibility as large-scale storage if given the proper incentives. However, due to the market power most data centers maintain, it is difficult to design programs that are efficient for data center demand response. To that end, we propose that prediction-based pricing is an appealing market design, and show that it outperforms more traditional supply function bidding mechanisms in situations where market power is an issue. However, prediction-based pricing may be inefficient when predictions are inaccurate, and so we provide analytic, worst-case bounds on the impact of prediction error on the efficiency of prediction-based pricing. These bounds hold even when network constraints are considered, and highlight that prediction-based pricing is surprisingly robust to prediction error.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/2591971.2592004DOIArticle
http://dl.acm.org/citation.cfm?doid=2591971.2592004PublisherArticle
Additional Information:© 2014 ACM. This work was supported by NSF grants CCF 0830511, CNS 0911041, and CNS 0846025, DoE grant DE-EE0002890, ARO MURI grant W911NF-08-1-0233, Microsoft Research, Bell Labs, the Lee Center for Advanced Networking, and ARC grant FT0991594.
Funders:
Funding AgencyGrant Number
NSF CCF-0830511
NSFCNS-0911041
NSFCNS-0846025
Department of Energy (DOE)DE-EE0002890
Army Research Office (ARO)W911NF-08-1-0233
Microsoft ResearchUNSPECIFIED
Bell LabsUNSPECIFIED
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
Australian Research CouncilFT0991594
Subject Keywords:data center, demand response, prediction based pricing, power network
Classification Code:J.2 [ Computer Applications ]: Physical sciences and en- gineering
Record Number:CaltechAUTHORS:20161128-163510694
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20161128-163510694
Official Citation:Zhenhua Liu, Iris Liu, Steven Low, and Adam Wierman. 2014. Pricing data center demand response. In The 2014 ACM international conference on Measurement and modeling of computer systems (SIGMETRICS '14). ACM, New York, NY, USA, 111-123. DOI=http://dx.doi.org/10.1145/2591971.2592004
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72348
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:29 Nov 2016 04:31
Last Modified:29 Nov 2016 04:31

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