综合智慧能源2026，Vol.48Issue(9)：120-130,11.DOI:10.3969/j.issn.2097-0706.2026.09.010
绿电直连模式下风光储驱动的数据中心经济性分析
Economic analysis of wind-photovoltaic-storage-driven data centers under green power direct connection mode
摘要
Abstract
With the advancement of the"dual carbon"goals and the rapid development of the digital economy,the energy consumption of data centers continues to rise.The green power direct connection mode has become a vital pathway for data centers to achieve low-carbon transition.Taking Zhongwei in Ningxia as the research setting,time-series output models were established for wind and photovoltaic(PV)power generation based on NASA hourly meteorological data and the HOMER Pro platform.A comprehensive green power direct connection system model was constructed,consisting of PV power generation,wind power generation,battery energy storage,the public power grid,and a single-phase immersion liquid-cooled data center with an IT rated power of 1 000 kW.The system operated under the strategy of"self-generation for self-consumption,surplus electricity fed to the grid,and energy storage for regulation".Electricity price,carbon emission reduction,and financial evaluation models were established.With the minimization of the dynamic payback period(DPP)as the optimization objective,discrete optimization of wind,PV,and energy storage capacities was carried out subject to policy constraints that the proportion of green power should not be lower than 30%,the self-consumption rate of green power should not be less than 80%,and the proportion of surplus electricity fed to the grid should not exceed 20%.Under the baseline condition with a power usage effectiveness(PUE)of 1.10,the optimal configuration included 2 150 kW PV capacity,4 wind turbines(totaling 1 000 kW),and 2 520 kW·h energy storage capacity.The corresponding DPP was 9.71 years,and the 20-year cumulative net present value(NPV)reached 4.422 million yuan.Annual energy balance analysis showed that the total annual power consumption of the data center was 7.199 million kW·h,the self-consumed green power generated on-site was 3.998 million kW·h,the average green power proportion was approximately 55.5%,and the surplus electricity feed-in rate was around 7.8%,all of which complied with the policy constraints.Hourly analysis of typical weeks in winter and summer revealed the complementary operation characteristics of wind and PV power,and energy storage effectively mitigated output fluctuations.Sensitivity analysis with a variation range of±40%was conducted on six parameters:PV investment,wind power investment,energy storage investment,overall time-of-use electricity price level,surplus electricity feed-in tariff,and carbon trading price.The influencing factors ranked in descending order of influence were:overall time-of-use electricity price level,unit PV investment,unit wind power investment,carbon trading price,unit energy storage investment,and surplus electricity feed-in tariff.The time-of-use electricity price was the dominant influencing factor.A 40%reduction would result in the project being unable to recover its investment.PV and wind power investments together accounted for 86.7%of the initial investment.Carbon trading price,energy storage investment,and feed-in tariff had relatively limited impacts.Further comparison among three operating conditions with PUE values of 1.10,1.30,and 1.60 indicated that a lower PUE led to better project economic performance.When PUE increased from 1.10 to 1.60,the 20-year cumulative NPV decreased by approximately 9.36%,and the DPP increased by roughly 6.18%.This was mainly due to the substantial increase in annual capacity charges resulting from larger grid connection capacity required to accommodate elevated peak loads.These findings provide a quantitative reference for capacity planning and investment decision-making of data centers adopting the green power direct connection mode.关键词
算电协同/绿电直连/数据中心/容量优化/动态投资回收期/经济敏感性分析/电能利用效率Key words
computing-electricity coordination/green power direct connection/data center/capacity optimization/dynamic payback period/economic sensitivity analysis/power usage effectiveness分类
能源科技引用本文复制引用
程云龙,刘芸彤,崔诵笈,王星皓,李雪强,张志强,刘圣春..绿电直连模式下风光储驱动的数据中心经济性分析[J].综合智慧能源,2026,48(9):120-130,11.基金项目
国家自然科学基金项目(52476085) （52476085）
河北省自然科学基金项目(E2026404005) （E2026404005）
天津市自然科学基金项目(25JCYBJC00030) National Natural Science Foundation of China(52476085) （25JCYBJC00030）
Natural Science Foundation of Hebei Province(E2026404005) （E2026404005）
Tianjin Natural Science Foundation Project(25JCYBJC00030) （25JCYBJC00030）
