Reinforcement Learning Based Algorithm for the Maximization of EV Charging Station Revenue

Stoyan Dimitrov, Redouane Lguensat
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引用次数: 16

Abstract

This paper presents an online reinforcement learning based application which increases the revenue of one particular electric vehicles (EV) station, connected to a renewable source of energy. Moreover, the proposed application adapts to changes in the trends of the station's average number of customers and their types. Most of the parameters in the model are simulated stochastically and the algorithm used is the Q-learning algorithm. A computer simulation was implemented which demonstrates and confirms the utility of the model.
基于强化学习的电动汽车充电站收益最大化算法
本文提出了一种基于在线强化学习的应用程序,该应用程序可以增加连接到可再生能源的特定电动汽车(EV)站的收入。此外,所提出的应用程序适应了车站平均客户数量及其类型的变化趋势。模型中的大部分参数是随机模拟的,使用的算法是Q-learning算法。通过计算机仿真验证了该模型的有效性。
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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