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一种基于交通流分析和蒙特卡罗方法的新型插电式混合动力汽车时空模型。

A novel spatial-temporal model for charging plug hybrid electrical vehicles based on traffic-flow analysis and Monte Carlo method.

作者信息

Afshar Mostafa, Mohammadi Mohammad Reza, Abedini Mohamad

机构信息

Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.

Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran 1983969411, Iran.

出版信息

ISA Trans. 2021 Aug;114:263-276. doi: 10.1016/j.isatra.2020.12.051. Epub 2020 Dec 28.

Abstract

The increase of using electric vehicles (EVs) may increase power demand and therefore major effects on the power system. Therefore, if we do not have an appropriate program for utilizing and managing battery charging in the EVs, the charging process may coincide with the peak of power consumption and cause severe network problems. This paper deals with modeling the problem and estimating load consumption in EVs connected to the system. The EVs have been considered based on a random load and a probabilistic process. To manage the EVs, a traffic method called the spatial-temporal scheme, which uses the Monte Carlo algorithm, has been proposed. Also, the proposed method can be used to represent a model of electric vehicles changes in their battery charge and their need for charging at different times of a full day in different zones of the city. The proposed method has been simulated in the Matlab software and implemented for Hamedan province. The results show that using this method of estimation can improve the management of EVs.

摘要

电动汽车(EV)使用量的增加可能会增加电力需求,从而对电力系统产生重大影响。因此,如果我们没有一个合适的电动汽车电池充电利用和管理方案,充电过程可能会与用电高峰期重合,从而导致严重的电网问题。本文探讨了对该问题进行建模以及估算接入系统的电动汽车的负荷消耗。电动汽车被视为基于随机负荷和概率过程。为了管理电动汽车,提出了一种称为时空方案的交通方法,该方法使用蒙特卡罗算法。此外,所提出的方法可用于表示不同城市区域全天不同时间电动汽车电池电量变化及其充电需求的模型。所提出的方法已在Matlab软件中进行了模拟,并在哈马丹省实施。结果表明,使用这种估算方法可以改善电动汽车的管理。

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