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计及多元绿电消费与时空灵活性的算电协同优化OA

Optimization of Computing Power and Electricity Synergy Considering Diverse Green Electricity Consumption Modes and Spatio-Temporal Flexibility

中文摘要英文摘要

[目的]在"双碳"目标与"东数西算"战略的双重驱动下,数据中心作为高功率密度灵活性负荷,其绿色转型与电力系统的协同优化愈发关键.针对枢纽节点新建数据中心80%绿电使用的政策要求,旨在探明不同绿电消费方式与算力负荷灵活性对数据中心运行成本及碳排放的影响机理,为算力枢纽的资源规划与协同调度提供决策依据.[方法]首先构建了算力电力节点双向协同优化模型,统筹考虑负荷侧算力任务的时间与空间柔性特征以及多元绿电消费方式的物理与合同约束,包括绿电直连、购电协议(power purchase agreement,PPA)及网电补充.引入平准化度电成本(levelized cost of electricity,LCOE)与后果性碳排放因子作为双维度评价指标.针对甘孜地区算电融合项目群,设计了绿电直连比例从80%至20%梯度下降的仿真场景,并深入探究了数据中心负荷无灵活性、时间灵活、空间灵活及时空协同灵活4种方案下的运行特性.[结果]仿真分析表明,在80%绿色电力消费比例约束下数据中心的LCOE随绿电直连比例的下降呈现显著的"U型"演变特征,时空协同灵活性调度通过全维度的资源寻优,实现了系统经济性与环境效益的帕累托改进,是实现大规模算电融合项目群低碳经济运行的最优调度范式.[结论]所提模型及评估框架量化了物理直连与虚拟匹配的成本边界,并有效揭示灵活性策略的影响规律,对优化算力枢纽的数据中心配置具有参考价值.

[Objective]Driven by the carbon peaking and carbon neutrality goals and the strategy of national computing network to synergize east and west,data centers have become crucial high-density flexible loads,making the coordinated optimization of their green transition and power systems increasingly vital.Focusing on the policy requirement for new data centers at hub nodes to achieve 80%green electricity consumption,this paper aims to explore the impact mechanisms of diverse green electricity consumption modes and computing load flexibility on the operational costs and carbon emissions of data centers,providing a decision-making basis for resource planning and coordinated dispatching in computing hubs.[Methods]A bidirectional coordinated optimization model for computing-power nodes is constructed,comprehensively considering the temporal and spatial flexibility of computing tasks alongside the physical and contractual constraints of diverse green electricity consumption modes,including direct green energy connection,power purchase agreements(PPA),and grid power supplementation.The levelized cost of electricity(LCOE)and consequential carbon emissions are introduced as dual evaluation metrics.Using the integrated computing-power project group in the Ganzi region as a case study,simulation scenarios are designed with a gradient decrease in the direct green energy connection ratio from 80%to 20%,comparing PPA and grid supplementation strategies while exploring the operational characteristics of data centers under four schemes:no flexibility,temporal flexibility,spatial flexibility,and spatio-temporal synergistic flexibility.[Results]Simulation results indicate that under the 80%green electricity consumption constraint,the LCOE of data centers exhibits a significant"U-shaped"evolution as the direct green energy connection ratio decreases.The dispatching under the spatio-temporal synergistic flexibility achieves a"Pareto improvement"in both economic and environmental benefits through full-dimensional resource optimization,serving as the optimal dispatching paradigm for the low-carbon and economic operation of large-scale integrated computing-power clusters.[Conclusions]The proposed model and evaluation framework quantify the cost boundaries between physical connection and virtual matching and effectively reveal the impact laws of flexibility strategies,offering valuable reference for optimizing the configuration of data centers at computing hubs.

凃陈;潘萱颖;王欢;孟垚;戴璟;王骁宇

雅砻江流域水电开发有限公司,成都市 610051清华大学电机系,北京市 100084雅砻江流域水电开发有限公司,成都市 610051清华大学能源互联网创新研究院,北京市 100084清华大学能源互联网创新研究院,北京市 100084清华大学能源互联网创新研究院,北京市 100084

信息技术与安全科学

算电协同绿电消费方式时空灵活性后果性碳排放平准化度电成本(LCOE)

computing-power synergygreen electricity consumption modesspatio-temporal flexibilityconsequential carbon emissionslevelized cost of electricity(LCOE)

《电力建设》 2026 (7)

1-13,13

国家自然科学基金项目(52577116) This work is supported by National Natural Science Foundation of China(No.52577116).

10.12204/j.issn.1000-7229.2026.07.001

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