Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm

Q2 Energy
Di Zheng, Baobao Zheng
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引用次数: 0

Abstract

By arranging the charging facilities of electric vehicles reasonably, electric vehicle users can be guided to charge during the peak period of renewable energy generation, improving their ability to consume this energy. To layout electric vehicle charging facilities, a single charging station optimization configuration model is constructed to provide optimal configuration parameter references for subsequent charging facility layout optimization models. In the optimization model, the study considers charging load calculation, site selection, and capacity determination. To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. These three improvements include randomly updating inertia weights, introducing acceleration factors to replace learning factors, and introducing fast non-dominated sorting for better or worse selection, and improving the optimization ability of the algorithm by solving the crowding distance. The results showed that the maximum function values of the designed algorithm were 3.56 × 10–14, 5.32 × 100, and 1.08 × 101 for unimodal, multimodal, and composite functions, respectively, and the standard deviations of the algorithm were 2.01 × 10–14, 3.557 × 100, and 8.56 × 10–1, all of which were smaller than comparison algorithms. In a single charging station, the expected values of photovoltaic power generation, energy storage system, and charging piles were 500 kW, 56.45 kW/20163 kW, and 680 kW, respectively. In terms of charging station location and charging facility capacity, there should be 7 charging locations and charging facilities. In summary, the designed model has good performance, and the optimized model can layout charging facilities. The research results can better promote the consumption of renewable energy, lower the construction cost, and optimize the utilization rate of charging facilities.

考虑可再生能源消费能力增强和改进粒子群算法的电动汽车充电设施布局优化
合理安排电动汽车充电设施,引导电动汽车用户在可再生能源发电高峰期充电,提高用户使用可再生能源的能力。为布局电动汽车充电设施,构建单个充电站优化配置模型,为后续的充电设施布局优化模型提供最优配置参数参考。在优化模型中,研究考虑了充电负荷计算、站点选择和容量确定。针对优化模型,采用了粒子群算法,并从三个方面进行了改进。这三种改进包括随机更新惯性权值、引入加速因子代替学习因子、引入快速非支配排序进行优劣选择,以及通过求解拥挤距离提高算法的优化能力。结果表明,所设计算法的单峰、多峰和复合函数的最大函数值分别为3.56 × 10-14、5.32 × 100和1.08 × 101,标准差分别为2.01 × 10-14、3.557 × 100和8.56 × 10-1,均小于比较算法。在单个充电站中,光伏发电的期望值为500 kW,储能系统的期望值为56.45 kW/20163 kW,充电桩的期望值为680 kW。在充电站位置和充电设施容量方面,应该有7个充电地点和充电设施。综上所述,所设计的模型具有良好的性能,优化后的模型能够实现充电设施的布局。研究结果可以更好地促进可再生能源的使用,降低建设成本,优化充电设施的利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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