基于LCC和量子遗传算法的电动汽车充电站优化规划

HUANG Xiaoqing

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基于LCC和量子遗传算法的电动汽车充电站优化规划

更新时间：2025-08-13

- 基于LCC和量子遗传算法的电动汽车充电站优化规划
- Automation of Electric Power Systems Vol. 39, Issue 17, Pages: 176-182(2015)
- 作者机构：
  
  湖南大学电气与信息工程学院,湖南省,长沙市,410000
- 作者简介：
- 基金信息：
- DOI：
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- Published：2015
- 稿件说明：
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HUANG Xiaoqing. [J]. Automation of electric power systems, 2015, 39(17): 176-182.
DOI：

HUANG Xiaoqing. [J]. Automation of electric power systems, 2015, 39(17): 176-182. DOI：

摘要

电动汽车充电站优化规划是电动汽车与智能电网灵活互动的重要研究内容之一。面向电动汽车充电站运营周期

详细分析了充电站的成本效益及全寿命周期成本（LCC）的计算方法;基于上述工作

提出利用交通路网车流量信息估算充电站容量

以充电站运营商获得的净现值收益最大为优选目标

以交通路网车流量、电网电能质量和经济性、用户充电需求为约束条件

确定充电站的选址和容量;进一步地

提出了计及LCC的充电站优化规划模型

并采用量子遗传算法求解该模型。算例仿真表明

优化规划模型及其求解方法有效。

Abstract

Optimal planning of electric vehicle charging stations is an important research area in the study of flexible interaction between electric vehicle and smart grid. The calculation method of cost-benefit and life cycle cost of electric vehicle charging stations is analyzed in the operation period of electric vehicle charging stations

based on which

a method of calculating charging station capacity using the data from the traffic flow is proposed

and an optimal objective of the operator gaining best net present value is proposed. With the traffic flow

the power quality and economy of grid and charging demand of customer as constraints

the location and capacity of charging stations can be determined. In addition

the optimal planning model of charging stations considering life cycle cost theory is proposed

with the quantum genetic algorithm used to solve the model. The simulation of the example has confirmed that the optimal planning model and solving method are effective. This work is supported by National Key Technologies R&D Program (No. 2013BAA01B01) and National Natural Science Foundation of China (No. 51137003

No. 61104090).

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