EN基于电动汽车聚合充放电支撑的微网孤岛运行策略
Microgrid Island Operation Strategy Based on EV Aggregated Charge and Discharge Support
- 现代电力 2026年43卷第1期 页码：138-148
- 作者机构：
1. 国网北京市电力公司门头沟供电公司, 北京市 门头沟区,102300
2. 新能源电力系统国家重点实验室(华北电力大学), 北京市 昌平区,102206
- 作者简介：
[ "张志远(1985)，男，硕士，高级工程师，研究方向为智能配电网、韧性电网与低碳电力技术等，E-mail：18800067010@163.com" ]
[ "武永军(1980)，男，硕士，高级工程师，研究方向为电网技术管理、电力系统优化运行与电力市场分析研究等，E-mail：13601225963@139.com" ]
[ "李熙钦(1978)，男，硕士，高级工程师，研究方向为电网规划管理等，E-mail：li_xiqin@126.com" ]
[ "张靓(1975)，女，硕士，高级工程师，研究方向为电力营销与电动汽车柔性充电技术管理等，E-mail：zhanghuijiang@yl.xj.sgcc.com" ]
[ "聂珍存(1999)，男，硕士，研究方向为分布式能源系统保护与控制，E-mail：niezhenncepu@163.com" ]
[ "马静(1981)，男，博士，教授，通信作者，研究方向为电力系统稳定分析、稳定和控制等，E-mail：hdmajing@163.com" ]
- 基金信息：国网北京市电力公司重点科技攻关项目(520210220009)。
DOI：10.19725/j.cnki.1007-2322.2023.0369
中图分类号： 1-
纸质出版：2026
- 稿件说明：
移动端阅览
张志远, 武永军, 李熙钦, 等. 基于电动汽车聚合充放电支撑的微网孤岛运行策略[J]. 现代电力, 2026,43(1):138-148.
张志远, 武永军, 李熙钦, et al. Microgrid Island Operation Strategy Based on EV Aggregated Charge and Discharge Support[J]. 2026, 43(1): 138-148.
张志远, 武永军, 李熙钦, 等. 基于电动汽车聚合充放电支撑的微网孤岛运行策略[J]. 现代电力, 2026,43(1):138-148. DOI： 10.19725/j.cnki.1007-2322.2023.0369.
张志远, 武永军, 李熙钦, et al. Microgrid Island Operation Strategy Based on EV Aggregated Charge and Discharge Support[J]. 2026, 43(1): 138-148. DOI： 10.19725/j.cnki.1007-2322.2023.0369.
摘要
电动汽车在时空维度上的不确定性，给微网孤岛调度运行带来严峻挑战。针对该问题，从孤岛负荷恢复角度出发，提出一种基于电动汽车聚合充放电支撑的微网孤岛运行策略。首先，通过分析动态交通流模型，建立考虑出行需求和交通流时变下的电动汽车聚合功率控制模型，并基于蒙特卡洛方法刻画电动汽车功率边界。然后，利用置信度模型考虑风光机组出力和负荷不确定性，建立以恢复负荷价值与电动汽车离网荷电量最大为目标的孤岛恢复模型，并进行优化求解。最后，通过改进的公路微网系统进行验证，结果表明该方法能够在保证负荷恢复量的同时，提升电动汽车离网荷电量，显著增强微网孤岛运行弹性和供电支撑能力。
Abstract
The temporal and spatial uncertainties associated with electric vehicles (EVs) bring severe challenges to the island dispatching operation of microgrids. To address this issue
in this paper we propose a microgrid island operation strategy based on EV aggregated charge and discharge support from the perspective of island load recovery. Firstly
an EV aggregated power control model is established by analyzing the dynamic traffic flow model
considering time-varying travel demand and traffic flow. In addition
the power boundary of EV is analyzed based on Monte Carlo method. After that
the island recovery model is established by considering the uncertainty of the wind turbine output and load of the confidence model
so as to restore the load value and the maximum of the EV off-grid and power. Subsequently
the optimization solution is implemented. The improved highway microgrid system is ultimately employed for verification. The results indicate that the proposed optimal scheduling strategy can guarantee the load recovery amount
increase the off-grid charge of EVs
and significantly enhance the operation elasticity and power supply support capability of microgrid islands.
关键词
Keywords
references
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