NDLI: Data center demand response: avoiding the coincident peak via workload shifting and local generation

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Data center demand response: avoiding the coincident peak via workload shifting and local generation

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Data center demand response: avoiding the coincident peak via workload shifting and local generation

Content Provider	ACM Digital Library
Author	Chen, Niangjun Razon, Benjamin Liu, Zhenhua Wierman, Adam Chen, Yuan
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 our full paper 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 our full paper, 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.
Starting Page	341
Ending Page	342
Page Count	2
File Format	PDF
ISBN	9781450319003
DOI	10.1145/2465529.2465740
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-06-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Coincident peak pricing Data center Demand response Online algorithm Workload shifting
Content Type	Text
Resource Type	Article

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