Towards an open model for data center research: From CPU to cooling tower
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A4 Artikkeli konferenssijulkaisussa
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Date
2018-12-26
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Language
en
Pages
7
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Proceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018, pp. 4913-4919, Proceedings of the Annual Conference of the IEEE Industrial Electronics Society
Abstract
Data centers are important players in the energy infrastructure. Aiming at addressing environmental challenges, large data centers such as Facebook, Google, Yahoo, etc., are increasing share of green power in their daily energy consumption. Such trends drive research into new directions, e.g. sustainable data centers. The research often relies on expressive models that provides sufficient details however practical to re-use and expand There is a lack of available data center models that capture dynamics of the facility from the CPU to the cooling tower. It is a challenge to develop a model that allows to describe complete data center of any scale including its connection to the grid. This paper proposes such a model building on existing work. The challenge was to put the pieces of data center together and describe dynamics of each element so that interdependences between components and parameters are captured correctly and in sufficient details. The proposed model was used in the project "Data center microgrid integration" and proven to be adequate and important to support such study.Description
Keywords
Chiller, Cooling, Cooling tower, CRAH, Data center, Microgrid, Model, Server, Smart grid
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Citation
Zhabelova, G, Vesterlund, M, Eschmann, S, Vyatkin, V & Flieller, D 2018, Towards an open model for data center research : From CPU to cooling tower . in Proceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 ., 8591609, Proceedings of the Annual Conference of the IEEE Industrial Electronics Society, IEEE, pp. 4913-4919, Annual Conference of the IEEE Industrial Electronics Society, Washington, District of Columbia, United States, 21/10/2018 . https://doi.org/10.1109/IECON.2018.8591609