考虑需求响应的数据中心余热系统运行优化

王奎, 王振宇, 沈仁东, 陈天恒, 丁一

太阳能学报 ›› 2024, Vol. 45 ›› Issue (11) : 9-14.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (11) : 9-14. DOI: 10.19912/j.0254-0096.tynxb.2023-1039

考虑需求响应的数据中心余热系统运行优化

  • 王奎1,2, 王振宇1,2, 沈仁东3, 陈天恒4, 丁一4
作者信息 +

OPERATION OPTIMIZATION OF DATA CENTER WASTE HEAT SYSTEM CONSIDERING DEMAND RESPONSE

  • Wang Kui1,2, Wang Zhenyu1,2, Shen Rendong3, Chen Tianheng4, Ding Yi4
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文章历史 +

摘要

构建一种融合可再生能源的数据中心余热利用系统,实现余热的高效利用。同时,为进一步降低系统运行成本,引入基于用户侧柔性负荷调节的需求响应机制,研究动态削峰补贴价格下系统的运行表现。结果表明:选取补贴价格依次为0.149、0.141、0.190、0.145元/kWh时,系统取得最高净收益266158.4元,且随着蓄热装置容量的提升,系统净收益增长率由10.4%降低至1.6%,可再生能源消纳量呈现下降趋势。

Abstract

A waste heat utilization system for data centers integrating renewable energy is constructed, enabling efficient waste heat utilization. Additionally, to further reduce the system’s operating costs, a demand response mechanism based on user-side flexible load regulation is introduced to study the system’s performance under dynamic peak-shaving subsidy prices. The results show that when the subsidy prices are set to 0.149, 0.141, 0.190, 0.145 yuan/kWh respectively, the system achieves its highest net income of 266158.4 yuan. As the capacity of the heat storage device increases, the net income growth rate decreases from 10.4% to 1.6%, while renewable energy consumption shows a declining trend.

关键词

数据中心 / 可再生能源 / 余热利用 / 需求响应

Key words

data centers / renewable energy / waste heat utilization / demand response

引用本文

导出引用
王奎, 王振宇, 沈仁东, 陈天恒, 丁一. 考虑需求响应的数据中心余热系统运行优化[J]. 太阳能学报. 2024, 45(11): 9-14 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1039
Wang Kui, Wang Zhenyu, Shen Rendong, Chen Tianheng, Ding Yi. OPERATION OPTIMIZATION OF DATA CENTER WASTE HEAT SYSTEM CONSIDERING DEMAND RESPONSE[J]. Acta Energiae Solaris Sinica. 2024, 45(11): 9-14 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1039
中图分类号: TK01+9   

参考文献

[1] 华北电力大学. 华北电力大学与阿里巴巴实现全球首次数据中心与电力系统间协同调度[EB/OL].https://energy.ncepu.edu.cn/zxdt/yjydt/aa1a9f538ad3461f90f33704e2791695.htm.
North China Electric Power University. North China Electric Power University and Alibaba achieved the world’s first coordinated dispatching between data centers and power systems[EB/OL].https://energy.ncepu.edu.cn/zxdt/yjydt/aa1a9f538ad3461f90f33704e2791695.htm.
[2] HUANG Q H, SHAO S Q, ZHANG H N, et al.Development and composition of a data center heat recovery system and evaluation of annual operation performance[J]. Energy, 2019, 189: 116200.
[3] 周梅. 基于多规融合的供热规划策略研究[J]. 居舍, 2021(15): 173-174.
ZHOU M.Research on heating planning strategy based on multi planning integration[J]. Dwelling house, 2021(15): 173-174.
[4] 李金苡. 浅谈利用济南某数据中心余热的供暖方式[J]. 建筑热能通风空调, 2021, 40(9): 64-67.
LI J Y.Analysis of the supply heating utilization of Ji’nan data centre[J]. Building energy & environment, 2021, 40(9): 64-67.
[5] 黄若琳. 大型数据中心机房冷却系统研究与优化[D]. 重庆: 重庆大学, 2018.
HUANG R L.Research and optimization of cooling system in computer room of large data center[D]. Chongqing: Chongqing University, 2018.
[6] 李国柱, 崔美华, 黄凯良, 等. 数据中心余热利用现状及在建筑供暖中的应用[J]. 科学技术与工程, 2022, 22(26): 11287-11295.
LI G Z, CUI M H, HUANG K L, et al.Current situation of data center waste heat utilization and its application in building heating[J]. Science technology and engineering, 2022, 22(26): 11287-11295.
[7] XU Z W, LI H, XU W, et al.Investigation on the efficiency degradation characterization of low ambient temperature air source heat pump under partial load operation[J]. International journal of refrigeration, 2022, 133: 99-110.
[8] 张继红, 阚圣钧, 化玉伟, 等. 基于氢气储能的热电联供微电网容量优化配置[J]. 太阳能学报, 2022, 43(6): 428-434.
ZHANG J H, KAN S J, HUA Y W, et al.Capacity optimization of CHP microgrid based on hydrogen energy storage[J]. Acta energiae solaris sinica, 2022, 43(6): 428-434.
[9] 冯璐. 耦合储能的可再生能源系统优化研究[D]. 北京: 华北电力大学, 2021.
FENG L.Study on Optimization of renewable energy system with coupled energy storage[D]. Beijing: North China Electric Power University, 2021.
[10] 林涛, 刘航鹏, 赵参参, 等. 基于SSA-PSO-ANFIS的短期风速预测研究[J]. 太阳能学报, 2021, 42(3): 128-134.
LIN T, LIU H P, ZHAO S S, et al.Short-term wind speed prediction based on SSA-PSO-ANFIS[J]. Acta energiae solaris sinica, 2021, 42(3): 128-134.

基金

国家电网有限公司科技项目(5400-202112159A-0-0-00)

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