考虑V2H的智能社区能量交易方案

刘迪迪; 姚欣欣; 廖志贤; 杨文宇; 沈阳; 胡聪

您当前的位置：

首页 >

文章列表页 >

考虑V2H的智能社区能量交易方案

更新时间：2026-02-03

- 考虑V2H的智能社区能量交易方案
- Vol. 53, Issue 1, Pages: 71-81(2026)
- 作者机构：
  
  1. 广西师范大学广西类脑计算与智能芯片重点实验室
  2. 广西师范大学电子与信息工程学院
  3. 桂林学院理工学院
  4. 桂林电子科技大学广西自动检测技术与仪器重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM73
- Published：2026
- 稿件说明：
移动端阅览
[1]刘迪迪,姚欣欣,廖志贤,等.考虑V2H的智能社区能量交易方案[J].华北电力大学学报(自然科学版),2026,53(01):71-81+105+82-83.

刘迪迪, 姚欣欣, 廖志贤, et al. 考虑V2H的智能社区能量交易方案[J]. 2026, 53(1): 71-81.
[1]刘迪迪,姚欣欣,廖志贤,等.考虑V2H的智能社区能量交易方案[J].华北电力大学学报(自然科学版),2026,53(01):71-81+105+82-83. DOI：

刘迪迪, 姚欣欣, 廖志贤, et al. 考虑V2H的智能社区能量交易方案[J]. 2026, 53(1): 71-81. DOI：

摘要

针对含光伏(photovoltaic

PV)、电动汽车(electric vehicle

EV)及家庭电器负荷的智能社区，以车入户(vehicle to home

V2H)的形式将EV纳入家庭需求响应框架，利用EV的双向输能特性并考虑EV充/放电带来的电池容量退化成本，协同PV、电网的实时电价和用户需求的可容忍时延，基于Lyapunov优化理论提出随机环境下V2H用户的EV充/放电调度策略和每户家庭的负荷响应策略，最小化家庭用户的长期平均购电成本。并提出一种智能社区在线能量交易方案，旨在最小化智能社区总的购电成本、最大限度提高社区能源利用率。理论分析和仿真结果表明，所提算法无需实时电价、PV出力、用户负荷需求的先验概率信息，仅基于当前系统状态就可使优化目标趋于最优值，实现家庭用户的能量调度和家庭用户之间的能量共享，减少家庭购电成本，提高用户之间能量交易的灵活性。

Abstract

Aiming at the smart community containing photovoltaic(PV)

electric vehicle(EV) and household electrical loads

EVs are incorporated into the household demand response framework in the form of Vehicle to Home(V2H)

leveraging their bi-directional energy transmission capability of EVs while considering battery capacity degradation due to charging/discharging. Based on Lyapunov optimization theory

an EV charging/discharging scheduling strategy for V2H users and a household load response strategy are proposed under a stochastic environment

in coordination with PV

real-time electricity price and the tolerable delay of user's demand

to minimize the long-term average electricity purchase cost for households. Additionally

an online energy trading scheme for smart communities is proposed to minimize the total electricity purchase cost and maximize community energy utilization. Theoretical analysis and simulation results show that the proposed algorithm does not require a priori probabilistic information of real-time electricity price

PV output and user load demand. Instead

it achieves optimization objectives toward optimality and enables energy scheduling and sharing among households based solely on the current system state

thus reducing household electricity costs and enhancing the flexibility of energy trading.

关键词

Keywords

references

YU L,QIN S,ZHANG M,et al.A review of deep reinforcement learning for smart building energy management[J].IEEE Internet of Things Journal,2021,8(15):12046-12063.

HUSAIN I,OZPINECI B,ISLAM M S,et al.Electric drive technology trends,challenges,and opportunities for future electric vehicles[J].Proceedings of the IEEE,2021,109(6):1039-1059.

WU X,HU X,YIN X,et al.Stochastic optimal energy management of smart home with PEV energy storage[J].IEEE Transactions on Smart Grid,2018,9(3):2065-2075.

潘振宁，余涛，王克英.考虑多方主体利益的大规模电动汽车分布式实时协同优化[J].中国电机工程学报，2019,39(12):3528-3541.PAN Zhenning,YU Tao,WANG Keying.Decentralized coordinated dispatch for real-time optimization of massive electric vehicles considering various interests[J].Proceedings of the CSEE,2019,39(12):3528-3541 (in Chinese).

NAKANO H,NAWATA I,INAGAKI S,et al.Aggregation of V2H systems to participate in regulation market[J].IEEE Transactions on Automation Science and Engineering,2021,18(2):668-680.

孙伟卿，刘唯，裴亮，等.高比例可再生能源背景下考虑储能系统价值的储-输多阶段联合规划[J].高电压技术，2021,47(3):983-993.SUN Weiqing,LIU Wei,PEI Liang,et al.Multistage energy storage-transmission network joint planning considering the system value of energy storage under the background of high penetration renewable energy[J].High Voltage Engineering,2021,47(3):983-993 (in Chinese).

陈玥，刘锋，魏韡，等.需求侧能量共享：概念、机制与展望[J].电力系统自动化，2021,45(2):1-11.CHEN Yue,LlU Feng,WEl Wei,et al.Energy sharing at demand side:concept,mechanism and prospect automation of electric power systems[J].Automation of Electric Power Systems,2021,45(2):1-11 (in Chinese).

ZHANG R,CHEN X,YANG L.Flexible energy management protocol for cooperative EV-to-EV charging[J].IEEE Transactions on Intelligent Transportation Systems,2019,20(1):172-184.

刘顺桂，艾欣，王坤宇，等.考虑电动汽车参与的电力系统发电与备用协同风险决策模型[J].华北电力大学学报(自然科学版),2019,46 (4):54-62.LIU Shungui,Al Xin,WANG Kunyu,et al.Collaborative risk decision-making model for electric power generation and reserve determining considering participation of electric vehicles[J].Journal of North China Electric Power University (Natural Sciencet Edition),2019,46 (4):54-62 (in Chinese).

徐岩，王晨光.计及荷电状态效益的含电动汽车微电网优化调度[J].华北电力大学学报(自然科学版),2021,48 (03):14-21.XU Yan,WANG Chenguang.Optimal dispatching of microgrid with electric vehicles considering SOC benefit[J].Journal of North China Electric Power University (Natural Science Edition),2021,48 (3):14-21 (in Chinese).

WU W,LIN Y,LIU R,et al.Online EV charge scheduling based on time-of-use pricing and peak load minimization:properties and efficient algorithms[J].IEEE Transactions on Intelligent Transportation Systems,2022,23(1):572-586.

董明，李阳，戴建卓，等.智能电网下电动汽车和可再生能源的协同发展[J].电网与清洁能源，2017,33(11):105-111.DONG Ming,Ll Yang,DAl Jianzhuo,et al.A review on electric vehicles and renewable energy synergies in smart grid[J].Power System and Clean Energy,2017,33(11):105-111 (in Chinese).

陶莉，高岩，朱红波，等.有可再生能源和电力存储设施并网的智能电网优化用电策略[J].中国管理科学，2019,27(2):150-157.TAO Li,GAO Yan,ZHU Hongbo,et al.Optimal scheduling for smart grids with the integration of renewable resourcesand storage devices[J].Chinese Journal of Management Science,2019,27(2):150-157 (in Chinese).

PAL S,KUMAR R.Electric vehicle scheduling strategy in residential demand response programs with neighbor connection[J].IEEE Transactions on Industrial Informatics,2018,14(3):980-988.

吴界辰，艾欣，张艳，等.配售分离环境下高比例分布式能源园区电能日前优化调度[J].电网技术，2018,42(6):1709-1719.WU Jiechen ,AI Xin,ZHANG Yan,et al.Day-ahead optimal scheduling for high penetration of distributed energy resources in community under separated distribution and retail operational environment[J].Power System Technology,2018,42(6):1709-1719 (in Chinese).

胡洁，李培强，林仕满，等.考虑分时电价差异性和基于主从博弈的智能楼宇集群能量共享方法[J].电网技术，2021,45(12):4738-4750.HU Jie,Ll Peiqiang,LIN Shiman,et al.Energy-sharing method for smart building clusters cconsidering differences of time-of-use prices and based on master-slave game[J].Power System Technology,2021,45(12):4738-4750 (in Chinese).

于浩，沈运帷，林顺富，等.考虑用户心理的商业楼宇集群能量共享优化策略[J].电网技术，2022,46(11):4423-4436.YU HAO,SHEN Yunwei,LIN Shunfu,et al.Optimization strategies for energy sharing in commercial building clusters considering user psychology[J].Power System Technology,2022,46(11):4423-4436 (in Chinese).

刘振，孙媛媛，李亚辉，等.基于用户行为预测的分布式光伏智能社区需求响应策略[J].山东大学学报(工学版),2022,52(5):24-34.LIU Zhen,SUN Yuanyuan,LI Yahui,et al.Demand response strategy for distributed photovoltaic smart community based on model prediction of user behavior analysis[J].Journal of Shandong University (Engineering Edition),2022,52(5):24-34 (in Chinese).

曾洋，王军，杨燕翔，等.基于联盟博弈的智能小区能量共享与需求响应模型[J].南方电网技术，2021,15(12):28-35.ZENG Yang,WANG Jun,YANG Yanxiang,et al.Energy sharing and demand response model of intelligent community based[J].Southern Power Grid Technology,2021,15(12):28-35 (in Chinese).

NEELYM J.Stochastic network optimization with application to communication and queueing systems[M].San Rafael:Morgan & Claypool Publishers,2010.

刘迪迪，孙浩天，肖佳文，等.智能电网中终端用户的双向能量交易算法[J].西安电子科技大学学报，2021,48(3):131-137.LIU Didi,SUN Haotian,XIAO Jiawen,et al.Two-way energy trading algorithms for the end-user in the smart grid[J].Journal of Xidian University,2021,48(3):131-137 (in Chinese).

刘迪迪，杨益菲，杨玉荟，等.随机环境下电动汽车充电实时管理与优化控制算法[J].上海交通大学学报，2023,57(1):1-9.LIU Didi,YANG Yifei,YANG Yuhui,et al.Management and optimal control algorithm for electric vehicle charging in random environment[J].Journal of Shanghai Jiao Tong University,2023,57(1):1-9 (in Chinese).

BEER S,GOMEZ T,DALLINGER D,et al.An economic analysis of used electric vehicle batteries integrated into commercial building microgrids[J].IEEE Transactions on Smart Grid,2012,3(1):517-525.

LIU N,YU X,FAN W,et al.Online energy sharing for nanogrid clusters:a Lyapunov optimization approach[J].IEEE Transactions on Smart Grid,2018,9(5):4624-4636.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Operation strategy for battery swapping stations of electric vehicles in microgrid environment

Multi-stage optimal planning of electric vehicle charging facilities

Optimal Planning of Charging Station for Electric Vehicle Based on PSODE Algorithm

Optimized Layout of Charging Station for Electric Vehicle Based on Firefly Algorithm

Research on Comprehensive Performance Evaluation for Electric Vehicles Charging Stations

Related Author

WANG Jian

WEN Fu-shuan

ZHANG Chen-xi

YANG Ai-min

WEN Fu-shuan

WANG Gui-bin

HAN Wei-qiang

LI Zhiwei

Related Institution

South China University of Technology

Zhejiang University

Electric Power Research Institute of Fujian Electric Power Company Limited

Division of Electric Vehicle Service,State Grid Zhejiang Electric Power Company

College of Mechatronics and Control Engineering,Shenzhen University

AI问答

⁰