EN考虑V2H的智能社区能量交易方案
考虑V2H的智能社区能量交易方案
- 华北电力大学学报（自然科学版） 2026年53卷第1期 页码：71-81
- 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：国家自然科学基金资助项目(62061006);广西类脑计算与智能芯片重点实验室(BCIC-23-Z7);广西自动检测技术与仪器重点实验室基金(YQ23203);广西研究生教育创新计划项目(XYCSR2024092)
DOI：
中图分类号： TM73-
纸质出版：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.
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
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