电动公交车充换电站需求特性的分析及分布优化

发布时间：2018-03-15 17:27

本文选题：电动汽车　切入点：电动公交车　出处：《北京交通大学》2015年硕士论文　论文类型：学位论文

【摘要】：随着全球经济的快速发展,能源匮乏、环境污染与经济增长之间的矛盾日益加剧,电动汽车以其节能、清洁和环保等优势被各国广泛关注,并被作为解决这一矛盾的重要措施得到大规模推广。目前,国内外众多国家与城市都积极地扶持电动汽车的发展,各大汽车厂商也都积极参与其中。作为电动汽车能源补给的电动汽车充换电配套设施的规划和建设将直接影响与制约电动汽车的发展。因此,充换电配套设施的优化规划研究对电动汽车的发展进程有一定的现实意义。本文首先从电动汽车需求特性、行为特性以及充换电设施规划三个方面归纳了国内外的研究现状,结合充换电设施的基础与国内外充换电设施的建设现状,总结了充换电设施规划的内容与方法。提出了利用多重线性回归分析和电动汽车市场扩散的BASS模型相结合的方法,建立了电动公交车的未来市场保有量预测模型,并以北京为算例进行了实例分析。对实际示范运营的电动公交车充换电站的运行数据进行分析,得到电动公交车行驶特性及运营规律的模型,并设计了运营流程仿真方法,结合充电机的充电特性,以电动公交车的实际运营数据为参考依据,用python软件实现了充换电站的供电负荷仿真与预测。介绍了遗传优化算法的基本原理,建立了年均最小综合费用模型,考虑充电站的建设、运行费用和充换电站的规模,以前文预测的电动公交车保有量以及供电负荷为依据,采用遗传算法对模型进行优化求解,通过对计算结果的分析,证明本文的方法具有一定的有效性和合理性。
[Abstract]:With the rapid development of the global economy, energy shortage, the contradiction between environmental pollution and economic growth is becoming more and more serious. Electric vehicles have been widely concerned by many countries because of their advantages of energy saving, cleanliness and environmental protection. And has been widely promoted as an important measure to solve this contradiction. At present, many countries and cities at home and abroad are actively supporting the development of electric vehicles. All the major automobile manufacturers are also actively involved in it. The planning and construction of the matching facilities for charging and exchanging electric vehicles, which are the energy supply for electric vehicles, will directly affect and restrict the development of electric vehicles. The research on the optimal planning of charging and changing facilities is of practical significance to the development of electric vehicles. Firstly, this paper summarizes the domestic and foreign research status from three aspects of electric vehicle demand characteristics, behavior characteristics and charging and switching facilities planning, combined with the foundation of charging and switching facilities and the current situation of domestic and foreign charging and switching facilities. The contents and methods of charging and switching facilities planning are summarized. The method of combining multiple linear regression analysis with BASS model of electric vehicle market diffusion is put forward, and the prediction model of the future market quantity of electric bus is established. The example of Beijing is given. By analyzing the operation data of the electric bus charging and changing power station, the model of the driving characteristics and operation law of the electric bus is obtained, and the simulation method of the operation flow is designed, which combines the charging characteristics of the charger. Based on the actual operation data of electric bus, the simulation and prediction of power supply load of rechargeable power station are realized by python software. This paper introduces the basic principle of genetic optimization algorithm, establishes the annual minimum comprehensive cost model, considers the construction of charging station, the operation cost and the scale of charging and changing power station, the quantity of electric bus and the power supply load predicted in the previous paper. Genetic algorithm (GA) is used to optimize the model. The results show that the proposed method is effective and reasonable.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491.8

【参考文献】