考虑容量预测和服务半径的电动汽车充电站定价协同调度

Haixin Wang, Siyu Chen, Jiahui Yuan, Mingchao Xia, Zhe Chen, Gen Li, Komla Agbenyo Folly, Yunzhi Lin, Yiming Ma, Junyou Yang
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引用次数: 0

摘要

电动汽车充电站调度可以通过优化充电价格实现利润最大化。现有的调度方法大多强调集线器的利益,对站间协调和动态服务半径的考虑较少。可调度容量预测的准确性直接影响到聚合商的利润。另外,电站选择的不确定性对可调度容量预测精度的影响也被忽略了。为了解决这些问题,提出了一个基于定价的多充电站协调调度框架。该框架结合了动态服务半径和可调度容量预测模型。该框架包括联合决策下电动汽车充电站选择行为分析和充电站动态服务半径模型的建立。此外,将物理模型与基于长短期记忆网络的数据驱动方法相结合,构建了可调度容量预测模型。与基于峰谷定价的调度方法和基于stackelberg定价方法相比,该框架的应用提高了集成商的利润。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Pricing-based coordinated scheduling for multiple EV charging stations considering capacity prediction and service radius

Pricing-based coordinated scheduling for multiple EV charging stations considering capacity prediction and service radius

Pricing-based coordinated scheduling for multiple EV charging stations considering capacity prediction and service radius

Electric vehicle (EV) charging station scheduling can maximize profits by optimizing charging prices. Many existing scheduling methods emphasize aggregator profits and still have limited consideration of inter-station coordination and the dynamic service radius. The prediction accuracy of schedulable capacity indirectly affects the profits of aggregators. In addition, the prediction accuracy of schedulable capacity is affected by the uncertainty of station selection, which has also been neglected. To address these issues, a pricing-based coordinated scheduling framework for multiple charging stations is proposed. The propose framework incorporates a dynamic service radius and schedulable capacity prediction models. The framework includes an analysis of EV station selection behaviour under joint decision-making and the development of a dynamic service radius model for charging stations. Additionally, a schedulable capacity prediction model is constructed by integrating physical modelling with a data-driven approach based on long short-term memory networks. Compared with the peak-valley pricing-based schedule method and Stackelberg-based pricing method, the aggregator profit is enhanced by the application of the proposed framework.

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