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上海电力大学学报:2022,38(2):105-111,138
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基于差分进化算法的多目标优化V2B2模式的调度策略
(上海电力大学 电子与信息工程学院)
A Multi-Objective Optimization V2B2 Scheduling Strategy Based on Differential Evolution Algorithm
(School of Electronics and Information Engineering, Shanghai University of Electric Power)
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投稿时间:2021-04-13    
中文摘要: 分布式可再生能源的配置提高了家庭微电网的调度空间,有利于能源结构的改善,但同时也对主电网的稳定性构成了挑战。针对这一现状,提出了一种基于差分进化算法的多目标优化V2B2模式的调度策略。该方法基于电动汽车的移动性,利用电动汽车和蓄电池的充放电功率,实现了2个不同地理位置下微电网的统一调度,在优化用电成本的基础上,着重于光伏发电的储存和使用,由此降低光伏波动对主电网的影响。采用上海地区相关数据进行实验,结果证明,该方案在降低用电成本、提高光伏自消耗率以及降低负荷峰谷差方面均取得了良好的效果。
Abstract:The configuration of distributed renewable energy increases the scheduling space of the home microgrid,which is beneficial to the improvement of the energy structure.But it also threatens the stability of the main grid at the same time.In this situation,this paper proposes a multi-objective V2B2 scheduling strategy based on differential evolution algorithm,which is based on the mobility of electric vehicles and uses the charge and discharge power of electric vehicles and batteries to realize the integrated schedule of microgrids in two different geographical locations.On the basis of power cost optimization,it focuses on storage and use of photovoltaic power generation which reduces the impact of photovoltaic fluctuations on the main grid.Experiments have proven that the scheme has achieved good results in reducing electricity costs,increasing the self-consumption rate of photovoltaics,and reducing the peak-to-valley difference of the load by using data from the Shanghai area.
文章编号:202202001     中图分类号:TM743    文献标志码:
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引用文本:
赵倩,刘励行.基于差分进化算法的多目标优化V2B2模式的调度策略[J].上海电力大学学报,2022,38(2):105-111,138.
ZHAO Qian,LIU Lixing.A Multi-Objective Optimization V2B2 Scheduling Strategy Based on Differential Evolution Algorithm[J].Journal of Shanghai University of Electric Power,2022,38(2):105-111,138.