Research on the Design and Operation Optimization of Distributed Multi-Energy Systems for Data Centers

REN Xiaoxiao; LI Xiaolong; XUE Kai; WU Xuan; HAN Xiaoqu; WANG Jinshi; YAN Junjie

doi:10.7652/xjtuxb202501009

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Research on the Design and Operation Optimization of Distributed Multi-Energy Systems for Data Centers

更新时间：2026-01-06

- Research on the Design and Operation Optimization of Distributed Multi-Energy Systems for Data Centers
- Journal of Xi’an Jiaotong University Vol. 59, Issue 1, Pages: 93-104(2025)
- 作者机构：
  
  1.西安交通大学动力工程多相流国家重点实验室， 710049，西安
  2.中国电力工程顾问集团西北电力设计院有限公司， 710075，西安
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202501009
  CLC： TK9
- Received：16 April 2024，
  
  Online First：12 September 2024，
  
  Published：10 January 2025
- 稿件说明：
移动端阅览
REN Xiaoxiao, LI Xiaolong, XUE Kai, et al. Research on the Design and Operation Optimization of Distributed Multi-Energy Systems for Data Centers[J]. Journal of Xi’an Jiaotong University, 2025, 59(1): 93-104.
DOI：

REN Xiaoxiao, LI Xiaolong, XUE Kai, et al. Research on the Design and Operation Optimization of Distributed Multi-Energy Systems for Data Centers[J]. Journal of Xi’an Jiaotong University, 2025, 59(1): 93-104. DOI： 10.7652/xjtuxb202501009.

摘要

为实现数据中心的低碳转型和能效提升，提出了一种集成多种可再生能源和储能设备的多能互补分布式能源系统作为其供能系统。建立了包含生命周期成本、碳排放、能耗、电网购电率和热量浪费率等指标的优化目标体系。制定了两种考虑负荷特征的运行策略，采用改进的多目标蝗虫优化算法对系统容量配置进行求解。为了分析优化目标和运行策略对系统优化的影响，通过组合不同优化目标和运行策略形成了多种优化设计方案，采用层次分析法和熵权法确定评价指标的权重，并利用多准则妥协解排序法进行评价排序。针对青海省某数据中心的案例，获得其能源系统的优化设计与运行方案。研究表明：运行策略主要影响吸收式制冷机和地源热泵的容量，而优化目标主要影响储能设备的容量；在相同的运行策略下，增加优化目标可提升系统的综合性能；对于不同的方案，生命周期成本、碳排放、能耗等基础优化目标值变化较小，而电网购电率和热量浪费率变化较大；通过实施五目标优化，即在基础优化目标的基础上增加热量浪费率、电网购电率，系统的综合性能得到了显著提升，其中热量浪费率和电网购电率分别降低了62.30%和25.92%，可再生能源发电占比增加了2%。

Abstract

To achieve low-carbon transformation and energy efficiency improvement of data centers

a distributed multi-energy system that incorporates various renewable energy sources and energy storage devices is introduced as their energy supply system. Firstly

an optimization objective system comprising life cycle costs

carbon emissions

energy consumption

grid electricity purchase rate

and heat waste rate is established. Subsequently

two operation strategies considering load characteristics are developed

and an improved multi-objective grasshopper optimization algorithm is employed to determine the system capacity configuration. To analyze the impact of optimization objectives and operation strategies on system optimization

various optimized design schemes are formulated by combining different optimization objectives and operation strategies. The analytic hierarchy process and entropy weight method are used to assign weights to evaluation criteria

and the vlseKriterijumska optimizacija I kompromisno resenje (VIKOR) method is applied for evaluation ranking. A case study on a data center in Qinghai province is conducted to obtain its energy system optimal design and operation scheme. The results indicate that the capacities of the absorption chiller and the ground source heat pump are influenced by the operation strategy

while the capacity of the energy storage device is affected by the optimization objective. Under the same operation strategy

increasing the number of optimization objectives can enhance the overall performance of the system. The values of the fundamental optimization objectives such as life cycle costs

carbon emissions

and energy consumption show minor variations across different schemes

whereas the grid electricity purchase rate and heat waste rate exhibit significant changes. Through the implementation of five-objective optimization

which integrates heat waste rate and grid electricity purchase rate with the basic optimization objectives

the system's overall performance is notably enhanced. Specifically

the heat waste rate and grid electricity purchase rate are reduced by 62.30% and 25.92%

respectively

while renewable energy generation sees a 2% increase.

关键词

Keywords

references

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