电动汽车对低压住宅配电网的影响:概率分析

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2023-08-07 DOI:10.1049/stg2.12123
Matthias Hungbo, Mingchen Gu, Lasantha Meegahapola, Timothy Littler, Siqi Bu
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引用次数: 0

摘要

在过去的二十年里,电动汽车的数量迅速增长,原因有几个,例如减少交通部门碳排放的政策指令和电动汽车行业的技术进步。然而,这增加了电网的负载需求,尤其是在低压(LV)网络中,因为大多数电动汽车都是在电动汽车车主的场所充电的。本文使用概率建模框架研究了电动汽车对低压住宅配电网的影响。电动汽车充电功率的概率分布函数是使用英国电动汽车数据集推导的。该研究调查了多个电动汽车渗透率水平、电动汽车充电表示的不同概率分布函数、车辆到电网(V2G)、太阳能光伏发电以及太阳能光伏逆变器的无功电压能力。结果表明,随着配电网中电动汽车渗透率的增加,变压器负载显著增加,稳态电压水平下降。V2G对配电网产生了积极影响。对太阳能光伏发电的真实低压馈线进行的案例研究表明,光伏发电和光伏逆变器的无功功能有助于减少电动汽车充电和V2G的影响。
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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Impact of electric vehicles on low-voltage residential distribution networks: A probabilistic analysis

The past two decades have seen a rapid increase in electric vehicles (EVs) for several reasons, such as policy directives to reduce carbon emissions in the transport sector and technology advancements in the EV industry. However, this has increased the load demand on the power grid, especially in the low-voltage (LV) network, as most EVs are charged at EV owner premises. This paper investigates the impact of EVs on the LV residential distribution network using a probabilistic modelling framework. Probability distribution functions for EV charging power are derived using the United Kingdom (UK) EV dataset. The study has investigated multiple EV penetration levels, different probability distribution functions for EV charging representation, vehicle-to-grid (V2G), solar photovoltaic (PV) generation, and the volt-var capability of the solar-PV inverter. The results have shown that as EV penetration increases in the distribution network, there is a significant increase in transformer loading and a decrease in the steady-state voltage levels. V2G has positively impacted the distribution network. A case study carried out on a real LV feeder with solar-PV generation has shown how PV generation and volt-var functionality of the PV inverter help reduce the impact of EV charging and V2G.

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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
期刊最新文献
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