Publication Type

Journal Article

Version

acceptedVersion

Publication Date

12-2018

Abstract

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal operation of precision equipment, such as CPU/GPU chips and hard disk, in data center, but it would also impact the stability of the utility power grids operation. To solve this problem, this paper presents a novel tie-line power fluctuation smoothing algorithm with consideration of data center’s holistic demand response. The contributions of this paper are: (1) overcoming the limitations of treating IT load as uncontrollable workload in the traditional demand response research, we design a data center resource scheduling model to realize IT load demand response controllability; (2) two novel mechanisms are proposed: (i) the server cluster workload scheduling method with time shift mechanism, and (ii) the data center UPS (Uninterruptible Power Supply) energy storage dynamic response mechanism. (3) Combining these two mechanisms as holistic demand response of data center, we present a tie-line power fluctuation smoothing algorithm to improve power supply reliability, which is beneficial to both the high density and precision IT equipment in the data center and the utility power grid. In the experiments, the results show that the new algorithm can effectively regulate the tie-line power fluctuations under different server cluster utilization ranges and scenarios of large-scale penetration of distributed renewable energy scenarios. The new algorithm is hence able to contribute beneficially to the reliability and stability of intelligent industrial park micro-grid and utility power grids.

Keywords

Controllable load, Data center, Holistic demand response, Tie-line power control

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Applied Energy

Volume

231

First Page

277

Last Page

287

ISSN

0306-2619

Identifier

10.1016/j.apenergy.2018.09.093

Publisher

Elsevier

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1016/j.apenergy.2018.09.093

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