1.交直流智能配电网湖北省工程中心,湖北省武汉市 430072
2.武汉大学电气与自动化学院,湖北省武汉市 430072
3.香港理工大学电机与电子工程学系,香港 999077
王弘利(1999—),男,博士研究生,主要研究方向:电动汽车、电力系统低碳经济运行。E-mail:hongli_wang@whu.edu.cn
杨军(1977—),男,通信作者,博士,教授,博士生导师,主要研究方向:电力系统运行与控制、电动汽车。E-mail:JYang@whu.edu.cn
李高俊杰(1996—),男,博士后,主要研究方向:电动汽车优化调度、电力市场交易机制设计。E-mail:gaojunjie.li@polyu.edu.hk
收稿:2025-06-30,
修回:2025-11-09,
网络首发:2026-06-05,
纸质出版:2026-08-10
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王弘利,杨军,李高俊杰等.基于虚拟队列和参数随机微分演化的在线EV电碳套餐设计[J].电力系统自动化,2026,50(15):199-210.
WANG Hongli,YANG Jun,LIGAO Junjie,et al.Online Electricity-Carbon Package Design for Electric Vehicles Based on Virtual Queues and Stochastic Differential Evolution of Parameters[J].Automation of Electric Power Systems,2026,50(15):199-210.
王弘利,杨军,李高俊杰等.基于虚拟队列和参数随机微分演化的在线EV电碳套餐设计[J].电力系统自动化,2026,50(15):199-210. DOI: 10.7500/AEPS20250630009.
WANG Hongli,YANG Jun,LIGAO Junjie,et al.Online Electricity-Carbon Package Design for Electric Vehicles Based on Virtual Queues and Stochastic Differential Evolution of Parameters[J].Automation of Electric Power Systems,2026,50(15):199-210. DOI: 10.7500/AEPS20250630009.
电动汽车可作为潜在的支撑资源参与系统需求侧调节,但其高随机性、低个体容量及用户的心理特征等资源特殊性导致其实际可控性低,难以稳定聚合利用。为此,文中提出了基于虚拟队列和参数随机微分演化的在线电动汽车电碳套餐设计方法。首先,考虑电动汽车的电-碳双重属性和用户理性约束,构建了电动汽车充放电站运营商最优套餐设计模型。其次,针对电动汽车的时序耦合特性和随机需求特征,建立了需求匹配虚拟队列,并基于Lyapunov优化方法将离线套餐问题转化为在线问题进行解耦求解。然后,利用随机微分方程刻画用户行为偏好参数的演化特征,并基于粒子滤波法设计了实时参数捕捉-在线套餐求解的闭环反馈计算流程。最后,仿真验证了所提电碳套餐设计方法的有效性及合理性。
Electric vehicles (EVs) can serve as potential supportive resources to participate in demand-side regulation of power systems. Nevertheless
their inherent resource characteristics including high randomness
small individual rated capacity and diversified user psychological preferences lead to poor practical controllability
making stable aggregated utilization difficult. To address this issue
this paper proposes an online electricity-carbon package design method for EVs based on virtual queues and stochastic differential evolution of parameters. Firstly
an optimal package design model for charging and discharging station operators is established considering the dual electricity-carbon attributes of EVs and user rationality constraints. Secondly
aiming at the temporal coupling and stochastic demand features of EVs
the demand-matching virtual queues are constructed. And the offline package problem is decoupled and converted into an online problem via Lyapunov optimization. Then
stochastic differential equations are adopted to characterize the evolutionary law of user behavioral preference parameters
and a closed-loop feedback calculation process integrating real-time parameter identification and online package solution is developed with the particle filter algorithm. Finally
the simulations verify the effectiveness and rationality of the proposed electricity-carbon package design method.
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