Optimal operation method of energy storage system in a data center based on MDP-ADMM algorithm

doi:10.19799/j.cnki.2095-4239.2023.0018

Abstract

Abstract:

This study proposed an optimal operation method for energy storage systems in the data center, based on the Markov decision process, and an alternating direction multiplier method to alleviate the problems of the high comprehensive operating cost of the data center and large load fluctuations on the grid side. First, the basic structure, the power consumption characteristics of the primary devices, and the load time-shifting characteristics of the data center are analyzed. Second, considering the power supply reliability of the data center, the charge and discharge power limit, and the loss cost of the energy storage system, an optimal operation model is established to minimize the peak-to-valley load difference and comprehensive operating cost. Then, given the multi-time coupling characteristic, the Markov decision process is used to reconstruct the model, and the alternating direction multiplier method is used to solve the reconstructed problem. Finally, the simulation analysis of a large-scale data center is conducted in MATLAB, and the obtained results verify the rationality and effectiveness of the proposed optimal operation method.

Key words: data center, energy storage system, load shifting characteristic, Markov decision process, alternating direction multiplier method, optimization operation

CLC Number:

TM 911

Xuchang CHEN, Yufei WANG, Hua XUE. Optimal operation method of energy storage system in a data center based on MDP-ADMM algorithm[J]. Energy Storage Science and Technology, 2023, 12(6): 1890-1900.

Figures/Tables 12

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Table 1

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Table 2

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Table 3

Optimal results with different prediction errors"

预测误差	求解算法	综合运行成本/元	负荷峰谷差/kW
$σ = 0.1$	PSO	30741	1037
	ADMM	28164	967
	MDP-ADMM	25374	768
$σ = 0.2$	PSO	31943	1186
	ADMM	29759	1028
	MDP-ADMM	26637	807

Table 3

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求解算法	最优适应度值	平均适应度值	标准差	达到最优解次数占比/%
PSO	14.2	15.9	1.3	20
ADMM	12.6	14.1	1.1	35
MDP-ADMM	12.4	12.7	0.6	55

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