Urban distribution network reconfiguration strategy considering electric vehicles

LIU Shu; SHI Shanshan; ZHOU Zheng; JIA Shicheng; LIAO Kai

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Urban distribution network reconfiguration strategy considering electric vehicles

更新时间：2025-12-06

- Urban distribution network reconfiguration strategy considering electric vehicles
- Vol. 62, Issue 6, (2025)
- 作者机构：
  
  1. 国网上海市电力公司
  2. 西南交通大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：
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- Published：2025
- 稿件说明：
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LIU Shu, SHI Shanshan, ZHOU Zheng, et al. Urban distribution network reconfiguration strategy considering electric vehicles[J]. 2025, 62(6).
DOI：

LIU Shu, SHI Shanshan, ZHOU Zheng, et al. Urban distribution network reconfiguration strategy considering electric vehicles[J]. 2025, 62(6). DOI：

摘要

配电网故障直接关系到用户，提高其故障恢复能力具有重要意义。此外，随着电动汽车(electric vehicle，EV)的逐渐普及，其作为一种分布式储能单元在配电网故障恢复方面应用潜力巨大。文中提出利用停车场中EV与网络重构的配电网故障恢复策略。首先，根据停车场中EV停放时间分布特性，将停车场分为公共停车场及居民停车场，并对两类停车场进行EV充电行为建模。其次，利用蒙特卡洛对EV充电行为进行模拟以生成不同场景，并建立不同场景下参与故障恢复的EV出力模型。然后，以负荷损失最小为目标，构建考虑EV及网络重构的配电网故障恢复模型；最后，以IEEE 33节点为例进行仿真分析，验证所提策略的有效性。

Abstract

Distribution network faults are directly related to users

and it is important to improve its fault recovery capability. In addition

with the gradual popularity of electric vehicle (EV)

it has great potential to be used as a distributed energy storage unit for distribution network service restoration. This paper proposes a distribution network service restoration strategy using EVs in parking lots and network reconfiguration. Firstly

according to the characteristics of EV parking time distribution in parking lots

parking lots are divided into public parking lots and residential parking lots

and EV charging behaviors are modeled for both types of parking lots. Secondly

the EV charging behaviors are simulated using Monte Carlo to generate different scenarios

and the EV output power model involved in service restoration under different scenarios is established. Then

a service restoration model of the distribution network considering EV and network reconfiguration is constructed to minimize load loss. Finally

simulation analysis is performed with the IEEE 33-node as an example to verify the effectiveness of the proposed strategy.

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