电动汽车充电站功率需求建模

发布时间：2018-04-14 05:23

本文选题：电动出租车 + 电动公交车　；参考：《华北电力大学》2014年硕士论文

【摘要】：在科技部制定的电动汽车科技发展“十二五”规划中明确指出电动汽车在未来数年内将实现大规模运营,因而电动汽车的充电功率需求将对电网带来一定影响。因此在电动汽车规模化运行之前,必须提前开展电动汽车充电功率需求的研究和预测。对电动汽车充电站功率需求的研究是引导电动汽车进行有序充电的基础,对于以后电动汽车的推广和应用具有重大的意义。电动汽车按照使用需求分为不同类型,研究电动汽车的充电功率需求应该按照不同类型及其对应的充电模式进行分析。本文提出一种基于实际运行规律的电动公交车充电站功率需求模型以及电动出租车充电站的充电功率需求模型。对于行驶行为较为规律的电动公交车,统计了实际电动公交车充电站运行数据,从中分析出交通情况、车速、载客量等因素影响下的SOE0和进站时间,并建立对应的计算模型。对于电动出租车运行规律并不明显的情况下,基于随机过程中的泊松过程得到充电开始时间的随机分布序列,利用电池SOC0与充电服务时间之间的内在关系估算电动出租车需要的充电服务时间。在建立了电动汽车充电功率影响因素计算模型之后,结合各自电池的充电功率曲线建立起充电站的充电功率需求模型。最后利用本文提出的建模方法,以北京北土城电动公交车充电站及深圳福田电动出租车充电站相关数据为算例,进行了仿真分析,并对预测结果进行对比分析,证明了模型的有效性。本文还进一步提出了一种基于ARMA时间序列算法的电动汽车充电站运行状态预测模型及充电功率需求计算方法。对于建模的过程,首先定义了充电桩的5种状态来描述电动汽车充电站的运行规律,并利用ARMA算法理论基础建立充电站运行状态预测模型。其次,以延庆电动出租车充电站基础运行数据为例,对预测过程做出了详细说明,并对预测模型进行误差分析和模型评价,以此验证模型的可靠性。最后,利用正在充电状态时间序列及充电桩的额定充电功率计算得到了充电站预测的充电功率曲线,与实际充电功率曲线进行了对比分析证明了模型的有效性和适应性。本文研究分析了电动汽车的充电功率需求,从实际运行规律和预测算法两个方面分别建立电动汽车充电站功率需求模型。本文的方法对成熟运营的充电站以及只有短期历史数据的充电站都具有一定的适用性。充电功率需求建模为电动汽车对电网影响的衡量提供重要的参考,同时为电动汽车有序充电起到一定的指导作用。
[Abstract]:In the 12th Five-Year Plan for the Development of Electric vehicle Science and Technology made by the Ministry of Science and Technology, it is clearly pointed out that the electric vehicle will be operated on a large scale in the next few years, so the demand for charging power of the electric vehicle will have a certain impact on the power grid.Therefore, the research and prediction of electric vehicle charging power demand must be carried out in advance before the scale operation of electric vehicle.The research on the power demand of electric vehicle charging station is the basis of leading electric vehicle to charge in order, which is of great significance to the popularization and application of electric vehicle in the future.Electric vehicles can be divided into different types according to their use requirements. The research on the charging power demand of electric vehicles should be based on different types and their corresponding charging modes.This paper presents a power demand model for electric bus charging station and a charging power demand model for electric taxi charging station based on actual operation law.For the electric bus with regular driving behavior, the operation data of the charging station of the actual electric bus are counted, and the SOE0 and the incoming time under the influence of the traffic situation, speed, passenger load and other factors are analyzed, and the corresponding calculation model is established.Under the condition that the running rule of electric taxi is not obvious, the random distribution sequence of charging start time is obtained based on the Poisson process in the random process.The relationship between battery SOC0 and charging service time is used to estimate the charging service time of electric taxi.After the calculation model of the factors influencing the charging power of the electric vehicle is established, the charging power demand model of the charging station is established according to the charging power curve of the respective batteries.Finally, using the modeling method proposed in this paper, taking the Beijing Beitucheng electric bus charging station and Shenzhen Futian electric taxi charging station as examples, the simulation analysis is carried out, and the prediction results are compared and analyzed.The validity of the model is proved.Furthermore, this paper presents a ARMA time series algorithm based on the electric vehicle charging station operating state prediction model and charging power demand calculation method.For the modeling process, five states of charging pile are defined to describe the operation law of charging station of electric vehicle, and the prediction model of operation state of charging station is established on the basis of ARMA algorithm theory.Secondly, taking the basic operation data of Yanqing electric taxi charging station as an example, the prediction process is explained in detail, and the error analysis and model evaluation of the prediction model are carried out to verify the reliability of the model.Finally, the predicted charging power curve of the charging station is obtained by using the time series of the charging state and the rated charging power of the charging pile. The comparison with the actual charging power curve proves the validity and adaptability of the model.In this paper, the charging power demand of electric vehicle is studied and analyzed, and the power demand model of charging station of electric vehicle is established from two aspects of actual operation law and prediction algorithm.The method proposed in this paper is applicable to both mature charging stations and charging stations with only short-term historical data.The modeling of charging power demand provides an important reference for measuring the impact of electric vehicles on the power grid and plays a guiding role in the orderly charging of electric vehicles.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U469.72;TM910.6

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