电动出租车日充电负荷估算方法

LI Yafen

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电动出租车日充电负荷估算方法

更新时间：2025-08-13

- 电动出租车日充电负荷估算方法
- Automation of Electric Power Systems Vol. 38, Issue 10, Pages: 55-60(2014)
- 作者机构：
  
  北京交通大学电气工程学院,北京市,100044
- 作者简介：
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- DOI：
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- Published：2014
- 稿件说明：
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LI Yafen. [J]. Automation of electric power systems, 2014, 38(10): 55-60.
DOI：

LI Yafen. [J]. Automation of electric power systems, 2014, 38(10): 55-60. DOI：

摘要

相较于传统燃油出租车，电动出租车具有无尾气排放、无噪音污染、运行成本低等优点，已在多个城市试点使用。电动出租车规模化发展后，其充电功率需求将相应提高并对电网产生一定影响。文中从出租车的运行模式和行驶特性出发，考虑换班制、用餐、夜间运行等对出租车充电开始时刻和日行驶里程的影响，分析对比了出租车与私家车的充电行为，并由此建立了出租车日充电负荷的分段概率估算模型，采用蒙特卡洛仿真方法求得电动出租车的日充电负荷。根据深圳市出租车的充电运营数据，采用充电负荷的分段概率估算模型估算出租车充电负荷并与实际负荷对比，结果表明该建模方法具有可信性。

Abstract

Compared to traditional fuel taxis

electric taxis have been used in several cities with the advantage of no emissions

no noise pollution

and low operating costs

etc. After the large-scale utilization of electric taxis

the charging power will increase and have an effect on the power grid. The charging behavior of electric taxis and private cars is compared based on the running mode and driving characteristics of a taxi while considering the influences of the shifts

dining

and night shift on taxi charging timing and mileages. A segmental probability estimation model is built accordingly. The daily charging load of electric taxis is solved using Monte Carlo simulation. According to the electric taxi charging operation data of Shenzhen city

the estimated electric taxi charging load is obtained by the segmental probability estimation model and compared with the actual load. Results show the validity of the segmental probability estimation model.

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