中国电机工程学报2025，Vol.45Issue(11)：4201-4215,15.DOI:10.13334/j.0258-8013.pcsee.240279
基于用户响应意愿结果导向的V2G参数配置策略及其优化调度应用
User Response-driven V2G Parameter Configuration Strategy and Its Application on Optimization Scheduling
摘要
Abstract
Unreasonable settings of parameters such as current rate and discharge depth in the vehicle-to-grid(V2G)may lead to undesirable behaviors such as deep discharge and high-rate charging/discharging.This not only exacerbates the additional battery degradation but also diminishes the user's willingness to participate in V2G.To address this issue,this paper first proposes a user willingness-oriented V2G parameter configuration strategy.Based on the fuzzy logic system and the relationship between V2G parameters and users,a membership function construction method is derived.Subsequently,a quantitative evaluation model for user response willingness considering multiple parameter factors is developed.V2G parameters are set based on the quantified results to enhance user response willingness.Considering that multiple factors such as V2G parameters,scheduling cycle,vehicle off-grid time,and state of charge(SOC)will affect the V2G response capacity,the classification criteria are defined by analyzing the risk scenarios such as overcharging or over-discharging of battery and incapability to meet user charging demands that may be caused by multiple factors.Furthermore,a power aggregation model based on classification criteria is proposed to capture the response capacity.Finally,the simulation results demonstrate that the proposed strategy not only enhances user willingness to respond but also significantly reduces additional battery degradation caused by the V2G scheduling process.关键词
响应意愿/隶属度函数/车网互动参数/分类判据/电池损耗Key words
response willingness/membership function/vehicle-to-grid(V2G)parameters/classification criteria/battery degradation分类
动力与电气工程引用本文复制引用
黎博,彭心富,代伟,谢代钰..基于用户响应意愿结果导向的V2G参数配置策略及其优化调度应用[J].中国电机工程学报,2025,45(11):4201-4215,15.基金项目
国家自然科学基金项目(52107082) （52107082）
广西科技基地和人才专项(2022AC21257).Project Supported by National Natural Science Foundation of China(52107082) （2022AC21257）
Project Supported by Specific Research Project of Guangxi for Research Bases and Talents(2022AC21257). （2022AC21257）
