DocumentCode
3089365
Title
Adaptive Power Management for Data Center in Smart Grid Environment
Author
Kaewpuang, Rakpong ; Chaisiri, Sivadon ; Niyato, Dusit ; Lee, Bu-Sung ; Wang, Ping
Author_Institution
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear
2012
fDate
10-13 July 2012
Firstpage
119
Lastpage
126
Abstract
We propose an adaptive power management (APM) algorithm for a data center with an objective to minimize the total cost of power bought from an electrical grid. This APM algorithm is developed for a smart grid environment which is envisioned to be a cooperative, responsive, and economical power system. In particular, APM algorithm takes the spot power price from an electrical grid, the power supply from a renewable power source, and users´ demand in terms of application workload processing into account when managing the power consumption. Therefore, an APM algorithm is considered to be the demand side management in a smart grid. To obtain an optimal decision of the APM algorithm, an optimization model based on stochastic programming with multi-stage recourse is developed. This optimization model considers various uncertainties and is able to determine the optimal solution for the APM algorithm. The APM algorithm is evaluated by numerical studies. The numerical results clearly show that the APM algorithm can minimize the power cost of a data center.
Keywords
computer centres; economics; power system management; smart power grids; stochastic programming; APM; adaptive power management; data center; economical power system; electrical grid; optimization; power supply; renewable power source; smart grid environment; stochastic programming; Adaptation models; Batteries; Optimization; Power demand; Random variables; Servers; Smart grids; Adaptive power management; data center; smart grid; stochastic programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Processing with Applications (ISPA), 2012 IEEE 10th International Symposium on
Conference_Location
Leganes
Print_ISBN
978-1-4673-1631-6
Type
conf
DOI
10.1109/ISPA.2012.24
Filename
6280283
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