基于机器学习的收费网络运营服务平台预约收费服务系统

Shu Su, Hui Yan, N. Ding
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引用次数: 2

摘要

本文提出了一种基于机器学习的电动汽车预留充电服务系统,该系统同时考虑了电力系统和交通系统的影响。提出的充电网络运营服务平台框架通过大规模电动汽车充电导航将电力系统与交通系统连接起来。“预留充电+消费”一体化服务模式对于应对电动汽车大规模整合具有重要意义。将充电时间窗口的概念应用于预留充电服务系统的电动汽车充电预测优化,设计了基于滑动时间轴的动态调度模型,使用户的充电过程摆脱排队时间和充电服务费周期的约束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning-Based Charging Network Operation Service Platform Reservation Charging Service System
This paper proposes a machine learning-based electric vehicle (EV) reserved charging service system, which takes into consideration the impacts from both the power system and transportation system. The proposed framework of charging network operation service platform links the power system with transportation system through the charging navigation of massive EVs. The "reserved charging + consumption" integrated service model would be great significant for dealing with large-scale integration of electric vehicles. It applies the concept of charging time window to optimization of EV charging prediction for the reserved charging service system, and designs a dynamic dispatching model based on sliding time axis to make charging process of users get rid of constraints of queuing time and charging service fee period.
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