LAPSE:2023.32061
Published Article
LAPSE:2023.32061
A Synthetic Approach for Datacenter Power Consumption Regulation towards Specific Targets in Smart Grid Environment
April 19, 2023
Abstract
With the large-scale grid connection of renewable energy sources, the frequency stability problem of the power system has become increasingly prominent. At the same time, the development of cloud computing and its applications has attracted people’s attention to the high energy consumption characteristics of datacenters. Therefore, it was proposed to use the characteristics of the high power consumption and high flexibility of datacenters to respond to the demand response signal of the smart grid to maintain the stability of the power system. Specifically, this paper establishes a synthetic model that integrates multiple methods to precisely control and regulate the power consumption of the datacenter while minimizing the total adjustment cost. First, according to the overall characteristics of the datacenter, the power consumption models of servers and cooling systems were established. Secondly, by controlling the temperature, different kinds of energy storage devices, load characteristics and server characteristics, the working process of various regulation methods and the corresponding adjustment cost models were obtained. Then, the cost and penalty of each power regulation method were incorporated. Finally, the proposed dynamic synthetic approach was used to achieve the goal of accurately adjusting the power consumption of the datacenter with least adjustment cost. Through comparative analysis of evaluation experiment results, it can be observed that the proposed approach can better regulate the power consumption of the datacenter with lower adjustment cost than other alternative methods.
Keywords
datacenter, demand response (DR), energy storage devices, operating cost, power regulation, smart grid
Suggested Citation
Zhao M, Wang X. A Synthetic Approach for Datacenter Power Consumption Regulation towards Specific Targets in Smart Grid Environment. (2023). LAPSE:2023.32061
Author Affiliations
Zhao M: State Key Laboratory of Plateau Ecology and Agriculture, Department of Computer Technology and Applications, Qinghai University, Xining 810016, China [ORCID]
Wang X: State Key Laboratory of Plateau Ecology and Agriculture, Department of Computer Technology and Applications, Qinghai University, Xining 810016, China [ORCID]
Journal Name
Energies
Volume
14
Issue
9
First Page
2602
Year
2021
Publication Date
2021-05-02
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14092602, Publication Type: Journal Article
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LAPSE:2023.32061
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https://doi.org/10.3390/en14092602
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