不确定因素下基于主从博弈的电动汽车参与综合能源系统优化调度

王开艳; 刘浩宇; 党建; 贾嵘; 何恒祥

doi:doi:10.19912/j.0254-0096.tynxb.2024-1104

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

不确定因素下基于主从博弈的电动汽车参与综合能源系统优化调度

更新时间：2025-12-17

- 不确定因素下基于主从博弈的电动汽车参与综合能源系统优化调度
- Issue 10, Pages: 516-525(2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1104
  CLC： M732
- Published Online：31 October 2025，
  
  Published：31 October 2025
- 稿件说明：
移动端阅览
王开艳, 刘浩宇, 党建, et al. 不确定因素下基于主从博弈的电动汽车参与综合能源系统优化调度[J]. 2025, (10): 516-525.
DOI：

王开艳, 刘浩宇, 党建, et al. 不确定因素下基于主从博弈的电动汽车参与综合能源系统优化调度[J]. 2025, (10): 516-525. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1104.

摘要

为实现综合能源系统（IES）和电动汽车入网（V2G）充电站的互利共赢

提出一种不确定因素下V2G充电站参与综合能源系统运行的主从博弈双层优化方法。首先

将综合能源系统设定为上层领导者、V2G充电站设定为下层跟随者

以IES运行成本最小为目标

通过制定各时段充放电价格引导下层V2G充电站调整充放电功率;下层以V2G充电站总充电成本最小为目标

根据上层制定的价格信息做出反应

从而构建主从博弈模型。然后基于多场景法

引入条件风险价值（CVaR）模型用以评估风电和光伏功率不确定性引起的运行风险损失。基于Karush-Kuhn-Tucker（KKT）条件与强对偶定理

将主从博弈双层模型转化为单层混合整数线性规划模型

通过求解其纳什均衡解获得最优定价方案及调度运行方案。结果表明

所建模型可兼顾IES和V2G充电站不同主体的经济性

有效平衡了运行成本和风险成本

同时保证了新能源消纳

促进了碳减排。

Abstract

To achieve mutual benefit between integrated energy systems （IES） and Vehicle-to-Grid（V2G） charging stations

a bilevel optimization method based on a leader-follower game under uncertain factors is proposed. Firstly

the IES is set as the upper-level leader and the V2G charging station as the lower-level follower. The objective of the upper level is to minimize the operating cost of the IES by formulating time-varying charging and discharging prices to guide the lower-level users in adjusting the charging and discharging power of the V2G charging station. The lower level aims to minimize the total charging cost of the V2G charging station and responsed based on the price information set by the upper level

thus constructing a leader-follower game model. Then

based on the multi-scenario method

the conditional value-at-risk （CVaR） is introduced to measure the risk loss caused by the uncertainty of wind and solar power output on system operation. Using the Karush-Kuhn-Tucker conditions and strong duality theorem

the original bilevel game model is transformed into a single-level mixed-integer linear programming problem to compute the Nash equilibrium solution

thereby obtaining the optimal operation and pricing scheme. Results show that the proposed method can balance the economic interests of different entities within the IES and V2G charging stations

achieve a balance between operating costs and risk costs

ensure the consumption of renewable energy and promote carbon reduction.

关键词

Keywords

references

朱西平, 江强, 钟宇, 等. 计及前瞻风险的综合能源系统低碳经济调度优化[J]. 太阳能学报, 2023, 44(6): 113-121.

安源, 苏瑞, 郑申印, 等. 计及碳交易和源-荷侧资源的综合能源系统低碳经济优化[J]. 太阳能学报, 2023, 44(11): 547-555.

李晓易, 谭晓雨, 吴睿, 等. 交通运输领域碳达峰、碳中和路径研究[J]. 中国工程科学, 2021, 23(6): 15-21.

VAGROPOULOS S I, BALASKAS G A, BAKIRTZIS A G.An investigation of plug-in electric vehicle charging impact on power systems scheduling and energy costs[J]. IEEE transactions on power systems, 2017, 32(3): 1902-1912.

杨镜司, 秦文萍, 史文龙, 等. 基于电动汽车参与调峰定价策略的区域电网两阶段优化调度[J]. 电工技术学报, 2022, 37(1): 58-71.

王璐瑶, 刘卫亮, 刘长良, 等. 计及电-热-氢负荷与动态重构的主动配电网优化调度[J]. 太阳能学报, 2025, 46(1): 460-471.

肖秋瑶, 杨騉, 宋政湘. 考虑碳交易和电动汽车充电负荷的工业园区综合能源系统调度策略[J]. 高电压技术, 2023, 49(4): 1392-1401.

高爽, 戴如鑫. 电动汽车集群参与调频辅助服务市场的充电调控策略[J]. 电力系统自动化, 2023, 47(18): 60-67.

王义, 靳梓康, 王要强, 等. 考虑电动汽车共享储能特性的园区综合能源系统低碳运行[J]. 电力系统自动化, 2024, 48(5): 21-29.

颜宁, 马广超, 李相俊, 等. 考虑跨季节性储能的园区综合能源系统低碳经济调度方法[J]. 高电压技术, 2023, 49(10): 4182-4191.

张虹, 张瑞芳, 周建丞, 等. 基于主从博弈和混合碳政策的园区综合能源系统低碳经济调度[J]. 太阳能学报, 2023, 44(9): 9-17.

华昊辰, 吴浩星, 陈星莺, 等. 考虑用能经济性与用户满意度灵活协同的综合能源系统双层优化[J]. 电网技术, 2024, 48(10): 4174-4188.

韩丽, 喻洪波, 王冲, 等. 考虑建筑物热惯性的综合能源系统主从博弈协调优化策略[J]. 太阳能学报, 2024, 45(9): 197-209.

王开艳, 梁岩, 贾嵘, 等. 不确定环境下基于纳什谈判的含掺氢燃气综合能源多微网两阶段优化调度[J]. 电网技术, 2023, 47(8): 3141-3159.

王秋杰, 亓浩, 谭洪, 等. 考虑碳市场风险的热电联产虚拟电厂低碳调度[J]. 电力自动化设备, 2024, 44(10): 8-15.

孙毅, 李飞, 胡亚杰, 等. 计及条件风险价值和综合需求响应的产消者能量共享激励策略[J]. 电工技术学报, 2023, 38(9): 2448-2463.

周亦洲, 孙国强, 黄文进, 等. 计及电动汽车和需求响应的多类电力市场下虚拟电厂竞标模型[J]. 电网技术, 2017, 41(6): 1759-1767.

YIN Y, HE C, LIU T Q, et al.Risk-averse stochastic midterm scheduling of thermal-hydro-wind system: a network-constrained clustered unit commitment approach[J]. IEEE transactions on sustainable energy, 2022, 13(3): 1293-1304.

SU S, LI Z N, JIN X L, et al.Bi-level energy management and pricing for community energy retailer incorporating smart buildings based on chance-constrained programming[J]. International journal of electrical power & energy systems, 2022, 138: 107894.

李亚鹏, 赵麟, 王祥祯, 等. 不确定碳-电耦合市场下梯级水电双层竞价模型[J]. 电力系统自动化, 2023, 47(20): 83-94.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

ELECTRICITY-HEAT-GAS COOPERATIVE OPTIMAL OPERATION STRATEGY OF INTEGRATED ENERGY SYSTEM BASED ON COOPERATIVE GAME

STUDY ON LOW-CARBON ECONOMIC OPTIMAL SCHEDULING MODEL OF COMMUNITY INTEGRATED ENERGY SYSTEM

OPTIMIZATION OF THERMOELECTRIC INTERACTION STRATEGRY OF COMMUNITY INTEGRATED ENERGY SYSTEM BASED ON BUILDING PHOTOVOLTAIC

电碳市场下考虑共享储能的多主体综合能源系统主从博弈优化运行

Related Author

李兴国

任永峰

孟庆天

陈建

贺彬

方琛智

Zhu Rong

Ren Yongfeng

Related Institution

College of Energy and Power Engineering, Inner Mongolia University of Technology

Inner Mongolia Electric Power Research Institute of Inner Mongolia Power Group Co., Ltd.

School of Electrical and Information Engineering, Tianjin University

Hubei Provincial Collaborative Innovation Centre for New Energy Microgrid, China Three Gorges University

College of Electrical Engineering & New Energy, China Three Gorges University

AI问答

⁰