Multi-time scale optimization scheduling of active distribution network considering electric vehicle access

高金兰; 徐 爽; 李 凯

doi:10.3969/j.issn.1009-1831.2025.05.012

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Multi-time scale optimization scheduling of active distribution network considering electric vehicle access

更新时间：2026-03-05

- Multi-time scale optimization scheduling of active distribution network considering electric vehicle access
- Vol. 27, Issue 5, (2025)
- 作者机构：
  
  东北石油大学电气信息工程学院,黑龙江,大庆,163318
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2025.05.012
  CLC：
- Published：2025
- 稿件说明：
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高金兰, 徐爽, 李凯. Multi-time scale optimization scheduling of active distribution network considering electric vehicle access[J]. 2025, 27(5).
DOI：

高金兰, 徐爽, 李凯. Multi-time scale optimization scheduling of active distribution network considering electric vehicle access[J]. 2025, 27(5). DOI： 10.3969/j.issn.1009-1831.2025.05.012.

摘要

随着分布式能源接入电网的比例不断增加，给电网的稳定性与运行成本带来了巨大的威胁。电动汽车作为常见的可调度资源，在促进可再生能源消纳方面有较大潜力。针对电动汽车与主动配电网之间的协同调度挑战，设计了一种多时间尺度优化调度模型。首先，以电价弹性模型为基础，考虑消费心理学因素并构建基于用户心理账户理论的分时电价模型，更好地引导电动汽车充放电；其次，根据用户是否签订激励协议分别进行日前与日内调度，考虑碳交易机制与主从博弈模型进行优化；最后，对蜉蝣算法改进以提高求解效率。Matlab软件证明提出模型与策略的有效性。

Abstract

The increase of the proportion of distributed energy connected to the grid brings huge threats to the stability and operation cost of the power grid. As common adjustable resource

the electric vehicle（EV）has a huge potential to promote the consumption of renewable energy. In order to solve the coordinated scheduling challenges between the electric vehicles and the distribution network

a multi-time scale optimal scheduling model is designed. Firstly

based on the elasticity model of electricity price

the time-of-use electricity price model on the user’s mental account theory is constructed considering the consumer psychological factors

so as to better guide the charging and discharging of electric vehicles. Secondly

the scheduling is carried separately before and within the day according to whether users sign the incentive agreement

and the optimization is carried out considering the carbon trading mechanism and the master-slave game model. Finally

the mayfly algorithm is improved to improve the solving efficiency. The effectiveness of the proposed model and strategy is proved by Matlab software.

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