Title :
Hierarchical Deployment and Control of Energy Storage Devices in Data Centers
Author :
Shuo Wang ; Yanzhi Wang ; Xue Lin ; Pedram, Massoud
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
Recent work has presented hierarchical deployment of energy storage devices (ESDs) at the data center, rack, and server levels within a data center, along with a corresponding control framework for peak power shaving and energy cost reduction under (time-of-use) dynamic energy pricing policies. However, the prior work does not use a realistic power delivery architecture of the data center with hierarchical ESD structure, and fails to account for some key characteristics such as rate capacity effect of batteries and power losses in various AC/DC and DC/DC converters in the power delivery architecture. This paper aims to overcome these shortcomings by (i) adopting a realistic power delivery architecture (from Intel) for centralized ESD structure as the starting point, (ii) presenting a novel power delivery architecture for data centers with hierarchical ESD structure, borrowing the best features of the centralized ESD structure from Intel and the distributed single-level ESD structures from Google and Microsoft, (iii) providing a mathematical framework for the optimal design (i.e., ESD provisioning) and control (i.e., Scheduling the charging and discharging of various ESDs) of the hierarchical ESD structure to minimize overall energy cost under dynamic energy pricing functions. This framework accounts for constraints on ESD volume (for each level) and the overall (annually amortized) capital cost, and power losses due to the rate capacity effect and conversion circuitry. The ESD design problem is solved by using a search-based algorithm, whereas the ESD control problem is formulated and solved as a hierarchical convex optimization algorithm. Experiments have been conducted using real Google cluster workload based on realistic data center specifications, demonstrating the effectiveness of the proposed optimal design and control framework.
Keywords :
cells (electric); cloud computing; computer centres; convex programming; cost reduction; power aware computing; pricing; search problems; AC-DC converters; DC-DC converters; ESD design problem; Google cluster workload; Intel; battery capacity effect; capital cost; centralized ESD structure; conversion circuitry; data centers; distributed single-level ESD structures; dynamic energy pricing functions; energy cost minimization; energy cost reduction; energy pricing policy; energy storage devices; hierarchical ESD structure; hierarchical convex optimization algorithm; mathematical framework; peak power shaving; power losses; rack; rate capacity effect; realistic power delivery architecture; search-based algorithm; server levels; Batteries; Distributed databases; Electrostatic discharges; Periodic structures; Servers; Uninterruptible power systems; data centers; energy storage devices (ESDs); hierarchical ESD structure;
Conference_Titel :
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4673-7286-2
DOI :
10.1109/CLOUD.2015.111