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作 者:徐霄 张腾 仇子文 高辉 XU Xiao;ZHANG Teng;QIU Ziwen;GAO Hui(College of Automation&College of Artificial Intelligence,Nanjing University of Posts and Telecommunications,Nanjing 210023 China)
机构地区:[1]南京邮电大学自动化学院、人工智能学院,江苏南京210023
出 处:《电力自动化设备》2025年第4期75-83,共9页Electric Power Automation Equipment
基 金:国家自然科学基金资助项目(52077107);南京邮电大学引进人才自然科学研究启动基金资助项目(NY220082)。
摘 要:为挖掘电动汽车(EV)集群参与下的多主体协同降碳潜力,提出一种考虑EV虚拟储能的源荷储日前协同降碳策略。建立EV个体充放电模型,提出一种基于闵可夫斯基和的EV集群虚拟储能可调度运行域评估模型,实现EV动态聚合;引入电碳交易、需求响应、议价能力指标与等效碳排放配额机制,构建配电网运营商、负荷聚合商与EV聚合商各主体决策模型,进而提出基于纳什谈判的源荷储协同降碳模型及其分布式求解算法;通过选取最恶劣典型场景下调度方案以解决源荷不确定性对日前调度方案可靠性的影响。算例验证结果表明该策略相比非合作运行策略,能够降低对上级电网的依赖,提升多主体联合收益,实现系统整体节能减排。To explore the carbon reduction potential of multi-agent collaboration under the participation of electric vehicle(EV)clusters,a day-ahead source-load-storage collaborative carbon reduction strategy considering EV-based virtual energy storages is proposed.The charging and discharging model of an individual EV is developed.A Minkowski-sum-based dispatchable operating region evaluation model for EV-based virtual energy storages is proposed,enabling the dynamic aggregation of EVs.By introducing the electric-carbon trading,demand response,bargaining power indicators,and equivalent carbon emission quota mechanisms,the decision-making models of distribution grid operators,load aggregators,and EV aggregators are constructed.Afterwards,a source-load-storage coordinated carbon reduction model based on Nash bargaining and its distributed solving algorithm are proposed.By selecting the dispatching strategy under the worst typical scenario,the impact of source-load uncertainty on the effectiveness of day-ahead dispatchable strategy is considered.The case study results show that compared to non-cooperative operation strategy,this strategy can reduce reliance on the upper grid,enhance joint benefits across multiple entities,and achieve overall energy saving and emission reduction.
关 键 词:电动汽车 日前调度策略 纳什谈判 碳交易 分布式优化
分 类 号:TM73[电气工程—电力系统及自动化]
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