| 基于LCC和量子遗传算法的电动汽车充电站优化规划 |
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| 引用本文： | 黄小庆,杨夯,陈颉,江磊,曹一家.基于LCC和量子遗传算法的电动汽车充电站优化规划[J].电力系统自动化,2015,39(17):176-182. |
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| 作者姓名： | 黄小庆 杨夯 陈颉 江磊 曹一家 |
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| 作者单位： | 湖南大学电气与信息工程学院, 湖南省长沙市 410000,国网山东省电力公司经济技术研究院, 山东省济南市 250000,湖南大学电气与信息工程学院, 湖南省长沙市 410000,湖南大学电气与信息工程学院, 湖南省长沙市 410000,湖南大学电气与信息工程学院, 湖南省长沙市 410000 |
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| 基金项目： | 国家科技支撑计划资助项目（2013BAA01B01）;国家自然科学基金资助项目（51137003,61104090） |
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| 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。
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| 关 键 词： | 充电站 优化规划 电网 量子遗传算法 全寿命周期成本 |
| 收稿时间： | 2015/3/23 0:00:00 |
| 修稿时间： | 2015/8/13 0:00:00 |
Optimal Planning of Electric Vehicle Charging Stations Based on Life Cycle Cost and Quantum Genetic Algorithm |
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| HUANG Xiaoqing,YANG Hang,CHEN Jie,JIANG Lei and CAO Yijia.Optimal Planning of Electric Vehicle Charging Stations Based on Life Cycle Cost and Quantum Genetic Algorithm[J].Automation of Electric Power Systems,2015,39(17):176-182. |
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| Authors: | HUANG Xiaoqing YANG Hang CHEN Jie JIANG Lei and CAO Yijia |
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| Affiliation: | College of Electrical and Information Engineering, Hunan University, Changsha 410000, China,Shandong Power Economic Research Institute, State Grid Shandong Electric Power Company, Jinan 250000, China,College of Electrical and Information Engineering, Hunan University, Changsha 410000, China,College of Electrical and Information Engineering, Hunan University, Changsha 410000, China and College of Electrical and Information Engineering, Hunan University, Changsha 410000, China |
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| 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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| Keywords: | charging station optimal planning power grid quantum genetic algorithm life cycle cost |
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