Demand Response and Open Automated Demand Response Opportunities for Data Centers
Date Published |
01/2010
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Publication Type | Report
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Authors | |
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LBL Report Number |
LBNL-3047E
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Abstract |
This study examines data center characteristics, loads, control systems, and technologies to identify demand response (DR) and automated DR (Open Auto-DR) opportunities and challenges. The study was performed in collaboration with technology experts, industrial partners, and data center facility managers and existing research on commercial and industrial DR was collected and analyzed. The results suggest that data centers, with significant and rapidly growing energy use, have significant DR potential. Because data centers are highly automated, they are excellent candidates for Open Auto-DR. "Non-mission-critical" data centers are the most likely candidates for early adoption of DR. Data center site infrastructure DR strategies have been well studied for other commercial buildings; however, DR strategies for information technology (IT) infrastructure have not been studied extensively. The largest opportunity for DR or load reduction in data centers is in the use of virtualization to reduce IT equipment energy use, which correspondingly reduces facility cooling loads. DR strategies could also be deployed for data center lighting, and heating, ventilation, and air conditioning. Additional studies and demonstrations are needed to quantify benefits to data centers of participating in DR and to address concerns about DR's possible impact on data center performance or quality of service and equipment life span. |
Notes |
Please cite this report as follows: Ghatikar, Girish, M.A. Piette, S. Fujita, A. T. McKane, J.Q Han, A. Radspieler, K.C. Mares, D. Shroyer. 2010. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy Commission, PIER Program and Pacific Gas and Electric Company (PG&E). |
Year of Publication |
2010
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Pagination |
56
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Institution |
Lawrence Berkeley National Laboratory
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City |
Berkeley
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Keywords | |
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Research Areas | |
File(s) | |
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