改进了对电动汽车充电站快速和慢速充电位置确定方法的人工蜂鸟算法
Sixia Fan1, Xiangyu Zeng1, Lanxin Li1
1School of Business, Shanghai Dianji University, Shanghai, China.
PloS one
|September 30, 2025
概括
本研究介绍了电动汽车 (EV) 充电站放置的优化模型,平衡成本并提高供应商,用户和电网的经济效率.
科学领域:
- 优化建模的优化建模
- 电动汽车充电基础设施的建设.
- 游戏理论应用 游戏理论应用
背景情况:
- 电动汽车 (EV) 充电基础设施的快速扩张带来了挑战.
- 高的选址成本来自于不平衡的快慢收费比率和多个利益相关方之间的复杂成本分配.
- 需要有效且具有成本效益的电动汽车充电站部署战略.
研究的目的:
- 为电动汽车充电基础设施的位置开发一个多目标优化模型.
- 用三方成本游戏解决成本分配问题,涉及供应商,用户和电网.
- 为了最大限度地降低施工/运营成本,用户时间损失,电网功率损失和电压偏差.
主要方法:
- 制定了一个基于三方成本游戏的四个目标优化模型.
- 嵌入式建设/运营成本,用户时间损失成本,电网功率损失成本和电压偏差成本.
- 利用改进的人工蜂鸟算法来解决优化模型.
主要成果:
- 拟议的模型有效地提高了电动汽车充电站位置的整体经济效率.
- 显著减少了用户时间损失和电网功率损失.
- 为实际应用验证了算法的稳定性和概括能力.
结论:
- 优化模型为战略性电动汽车充电站站点选择提供了有价值的框架.
- 这种方法提供了一个平衡的解决方案,考虑到供应商,用户和电网的经济利益.
- 突出了先进算法的潜力,解决复杂的基础设施规划问题.
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