A profit optimization framework of energy storage devices in data centers: Hierarchical structure and hybrid types

Xue Lin, Massoud Pedram, Jian Tang, Yanzhi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper investigates the hierarchical deployment and over-provisioning of energy storage devices (ESDs) in data ceners by (i) adopting a realistic power delivery architecture (from Intel) for centralized ESD structure as the starting point; (ii) presenting a novel and realistic power delivery architecture, borrowing the best features of the centralized ESD structure from Intel and distributed single-level ESD structures from Google and Microsoft, and supporting the case that different types of ESDs are employed for each of the data center, rack, and server levels; (iii) providing an optimal design (i.e., determining the ESD type, and ESD provisioning at each level) and control (i.e., scheduling the charging and discharging of various ESDs) framework to maximize the amortized profit of the hierarchical ESD structure. The amortized onetime capital cost (capex), operating cost (opex), and cost associated with battery aging and replacement are considered in the profit optimization. Constraints on ESD volume and realistic characteristics of ESDs and power conversion circuitries are accounted for in the framework. (iv) conducting experiments using real data center workload traces from Google based on realistic data center specifications, demonstrating the effectiveness of the proposed design and control framework.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 9th International Conference on Cloud Computing, CLOUD 2016
PublisherIEEE Computer Society
Pages640-647
Number of pages8
ISBN (Electronic)9781509026197
DOIs
StatePublished - Jan 17 2017
Event9th International Conference on Cloud Computing, CLOUD 2016 - San Francisco, United States
Duration: Jun 27 2016Jul 2 2016

Other

Other9th International Conference on Cloud Computing, CLOUD 2016
CountryUnited States
CitySan Francisco
Period6/27/167/2/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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  • Cite this

    Lin, X., Pedram, M., Tang, J., & Wang, Y. (2017). A profit optimization framework of energy storage devices in data centers: Hierarchical structure and hybrid types. In Proceedings - 2016 IEEE 9th International Conference on Cloud Computing, CLOUD 2016 (pp. 640-647). [7820327] IEEE Computer Society. https://doi.org/10.1109/CLOUD.2016.88