摘要
为应对电动汽车(EV)规模化接入综合能源系统(IES)带来的挑战,构建基于可再生能源的实时电价机制与双层协同优化框架,并提出改进型多目标向日葵算法(IMOSFO)用于求解该模型。结果表明,通过协调上层的容量配置与下层的充放电策略,系统年经济成本降低了13%,碳排放量和电网依赖度减少了31%,用户充电费用降低了25%。该模型能够有效提升可再生能源的消纳能力,缓解大规模电动汽车接入对电网的影响。
To address the challenges brought by the large-scale integration of electric vehicles(EVs)into the integrated energy system(IES),a real-time electricity price mechanism based on renewable energy and a two-layer collaborative optimization framework are constructed,and an improved multi-objective sunflower algorithm(IMOSFO)is proposed to solve this model.The results show that by coordinating the capacity configuration at the upper level with the charging and discharging strategies at the lower level,the annual economic cost of the system is reduced by 13%,carbon emissions and grid dependence are decreased by 31%,and the charging cost for users is reduced by 25%.This model can effectively enhance the consumption capacity of renewable energy and alleviate the impact of large-scale electric vehicle integration on the power grid.
作者
桂佩佩
李钰
GUI Peipei;LI Yu
出处
《节能》
2025年第8期22-27,共6页
Energy Conservation
关键词
需求响应
实时电价
综合能源系统
两层优化
向日葵算法
电动汽车
demand response
real-time electricity price
integrated energy system
two-layer optimization
sunflower algorithm
electric vehicle
