Optimal dispatching strategy and application of electric vehicle charge-exchange-storage integrated power plant

叶 婷; 邓 星; 黄 堃; 梁加本; 张智俊

doi:10.3969/j.issn.1009-1831.2021.04.013

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Optimal dispatching strategy and application of electric vehicle charge-exchange-storage integrated power plant

更新时间：2026-03-05

- Optimal dispatching strategy and application of electric vehicle charge-exchange-storage integrated power plant
- Vol. 23, Issue 4, (2021)
- 作者机构：
  
  1. 国网江苏省电力有限公司南京供电分公司,南京,210019
  2. 国电南瑞科技股份有限公司,南京,211100
  3. 南京邮电大学,南京,210023
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2021.04.013
  CLC：
- Published：2021
- 稿件说明：
移动端阅览
叶婷, 邓星, 黄堃, et al. Optimal dispatching strategy and application of electric vehicle charge-exchange-storage integrated power plant[J]. 2021, 23(4).
DOI：

叶婷, 邓星, 黄堃, et al. Optimal dispatching strategy and application of electric vehicle charge-exchange-storage integrated power plant[J]. 2021, 23(4). DOI： 10.3969/j.issn.1009-1831.2021.04.013.

摘要

随着电动汽车数目的增加，需要不断提升其能源优化管理策略，以充分发挥电动汽车潜能，实现低碳经济供电的目标。针对含电动汽车的充换储一体化电站，研究其预测能源优化管理问题。首先，基于电动汽车出行链特性分析，采用蒙特卡洛算法对电动汽车负荷量进行预测。然后，针对电动汽车充换储一体化电站、可中断负荷和分布式电站组成的虚拟电厂，以运行成本最小化即经济效益最大化构建综合目标函数，并利用基于改进的粒子群优化算法，对虚拟电厂的运行进行源荷储协同优化调度，以确定电动汽车充放电功率大小、储能电池充放电策略和可中断负荷的调度策略。最后，将该分布式能源优化策略应用到一产业园区中，仿真结果验证了该策略的有效性。

Abstract

With the increase of electric vehicles

it’s necessary to continuously improve the energy optimization management strategies in order to give full play to the potential of electric vehicles and achieve the goal of low - carbon economic power supply.The forecasting energy optimization management problem is studied for the electric vehicle charge-exchange-storage integrated pow-er station. Firstly

the Monte Carlo algorithm is used to predict the loads of electric vehicles based on the analysis of the characteristics of the electric vehicle travel chain. Then

aiming at the virtual power plant composed of the electric vehicle charge-exchange-storage integrated power station

interruptible load and distributed power station

a comprehensive objective function using the improved particle swarm optimization algorithm is built to optimize the virtual power station to minimize the operation cost and maximize the economic benefit. In order to determine the optimal charging and discharging power of the electric vehicle charging and storage integrated power station

the coordinated optimal scheduling of exchange power of electrical vehicle

storage and load is carried out. Finally

the distributed energy optimization strategy is applied to an industrial park

and the simulation results verify the effectiveness of the strategy.

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