综合智慧能源2026，Vol.48Issue(9)：14-28,15.DOI:10.3969/j.issn.2097-0706.2026.09.002
面向绿电消纳的交通-算力负荷灵活性可调潜力量化综述
Review of flexibility and adjustable potential quantification of transportation and computing loads for green power accommodation
摘要
Abstract
The high penetration of wind and photovoltaic power has shifted green power accommodation from an energy balance issue to the challenges of spatiotemporal source-load matching and flexible regulation.Emerging loads,including electric vehicles,battery swapping stations,energy replenishment stations for electric heavy-duty trucks,and data centers,have become important demand-side resources for supporting green power accommodation due to their spatiotemporal transfer and power regulation capabilities.The flexibility sources,constraint boundaries,and quantification methods for three types of transportation loads are reviewed.Conventional electric vehicles exhibit probabilistic aggregation capabilities based on safe state of charge(SOC)boundaries and parking time windows.Battery swapping stations provide station-level load transfer flexibility through battery inventories and decoupling of charging and swapping processes.Electric heavy-duty trucks provide centralized regulation capabilities in mines,ports,and other scenarios.The adjustable potential of all three load types can be characterized by upper and lower power limits,transferable energy,and SOC boundaries.However,the response duration should be corrected by considering constraints such as vehicle arrival and departure times,transport tasks,and station capacity.On the computing side,data center load flexibility is analyzed from three aspects:task time transfer,spatial migration,and equipment-side power regulation.Deferrable batch processing tasks,task migration across data centers,and dynamic voltage and frequency scaling provide regulation flexibility in the temporal,spatial,and power dimensions,respectively.However,all of these approaches are constrained by service-level agreements,network bandwidth,and equipment safety.The approaches for coordinated quantification are further summarized.A virtual energy storage model is used to unify the time transfer of transportation energy replenishment and the delay of computing tasks as equivalent charging and discharging behaviors,and to characterize temporal flexibility boundaries.Spatial flexibility is characterized based on transferable load capacity between nodes,and a cross-compensation model between transportation and computing loads is then proposed to explicitly describe the complementary regulation relationship between the two types of loads when one type is constrained.Representative scenarios are generated using Latin hypercube sampling and K-medoids clustering.Under a specified confidence level,credible executable power,reduction coefficients,and response reliability rate are defined to enable credible quantification of theoretical potential.Existing studies indicate that transportation loads are suitable for providing short-term power response and local distribution network support,whereas computing loads have advantages in sustained regulation and cross-regional migration.Their coordination can form a composite flexible resource that integrates short-term rapid response,medium-and long-term continuous regulation,and cross-node load migration,thereby effectively improving the spatiotemporal matching between green power output and load demand.Theoretical adjustable potential can serve as a flexible resource available for grid scheduling only after correction for operating constraints and uncertainties.Existing research faces problems including inadequate unified modeling,insufficient quantification of credible adjustable potential,incomplete indicator systems,and inadequate validation in typical scenarios.Future efforts should focus on developing online technologies for credible potential calculation based on mechanism-data fusion and distributed intelligent regulation technologies under security and privacy constraints.关键词
绿电消纳/交通负荷/算力负荷/可调潜力/虚拟储能/时空协同/需求响应/算电协同Key words
green power accommodation/transportation load/computing load/adjustable potential/virtual energy storage/spatiotemporal coordination/demand response/computing-electricity coordination分类
能源科技引用本文复制引用
朱虹谕,张蕊,武晓栋,陈拓宇,陈敏,TAN Minghui,张冬冬..面向绿电消纳的交通-算力负荷灵活性可调潜力量化综述[J].综合智慧能源,2026,48(9):14-28,15.基金项目
国家重点研发计划项目(2026YFE0211200) （2026YFE0211200）
内蒙古自治区自然科学基金项目(2026QC0364,2026QC0321) （2026QC0364,2026QC0321）
国家自然科学基金项目(52677064) National Key R&D Program of China(2026YFE0211200) （52677064）
Inner Mongolia Natural Science Foundation(2026QC0364,2026QC0321) （2026QC0364,2026QC0321）
National Natural Science Foundation of China(52677064) （52677064）
