基于云计算平台的电动汽车有序充电监控系统研究

发布时间：2018-04-20 06:19

本文选题：电动汽车 + 区域电网　；参考：《华北电力大学》2015年硕士论文

【摘要】：经济的增长和社会的进步,带动人们生活水平提高的同时,也造成了深刻的能源环境问题,能源短缺和环境污染是当前人类社会面临的重大问题。电动汽车的产生和发展,为人类解决能源环境问题提供了新的思路。然而,大规模电动汽车的投入运行与接入电网,对城市交通、电网安全稳定等是一个重大挑战。本课题提出一种综合考虑电网侧电网负荷、充电公平性和用户侧便利性、快捷性等因素的多目标优化充电模型,依此模型对区域电网内电动汽车进行有序充电,在保证公平性的基础上,实现最优化有序充电,尽可能保证电网安全稳定运行、提升用户体验和节约成本。运用迭代法、贪心法、优先级法和多级反馈队列等经典算法,解决多目标优化模型的最优解问题。区域电网电动汽车多目标优化充电模型的实现需要电力网、车联网、充电站(桩)联网及其他相关信息的融合。随着行业的发展,在多信息源融合的过程中,会产生海量异构化数据,呈大数据化,采用传统的单机串行化处理模式已经无法满足时间和空间上的需求,其存储和计算都将成为瓶颈。因此,本课题提出并实现了基于云计算平台的电动汽车有序充电监控系统。利用Hadoop开源云计算平台,组建计算集群,实现此类大数据的并行化处理。系统以多目标优化充电模型为核心,设计系统功能,包括数据接收、数据实时与离线处理、数据展示等。设计系统物理和逻辑框架,依此框架搭建Hadoop云计算平台,利用HBase分布式数据库存储电网侧和用户侧数据,利用MapReduce编程框架实现基础性算法,并实现系统功能。课题按照提出问题-需求分析-模型设计-系统设计-系统实现的顺序逐步深入进行研究,提出、设计并实现基于云计算平台的电动汽车有序充电监控系统。
[Abstract]:The growth of economy and the progress of society bring about the improvement of people's living standard and at the same time cause profound problems of energy and environment. Energy shortage and environmental pollution are the major problems facing human society at present. The emergence and development of electric vehicles provide a new way for human beings to solve energy and environmental problems. However, the operation and connection of large-scale electric vehicles to the power grid is a major challenge to urban traffic, power grid safety and stability. In this paper, a multi-objective optimal charging model considering the load, charging fairness, convenience and rapidity of the power grid is proposed. According to this model, the electric vehicles in the regional power network are charged in an orderly manner. On the basis of fairness, we can realize the optimal and orderly charging, ensure the safe and stable operation of the power network as much as possible, improve the user experience and save the cost. The iterative method, greedy method, priority method and multilevel feedback queue are used to solve the optimal solution of multi-objective optimization model. The realization of multi-objective optimal charging model for electric vehicles in regional power grid requires the integration of power grid, vehicle network, charging station (pile) network and other related information. With the development of industry, mass isomerization data will be produced in the process of multi-information source fusion, and the traditional single-machine serialization processing mode can no longer meet the needs of time and space. Its storage and computing will become a bottleneck. Therefore, this paper proposes and implements an electric vehicle charging monitoring system based on cloud computing platform. Hadoop open-source cloud computing platform, set up a computing cluster to achieve this big data parallel processing. The system is based on the multi-objective optimized charging model. The functions of the system include data receiving, real-time and off-line data processing, data display and so on. The physical and logical framework of the system is designed, according to which the Hadoop cloud computing platform is built. The distributed database of HBase is used to store the data on the grid side and the user side, and the basic algorithm is realized by using the MapReduce programming framework, and the system functions are realized. According to the order of putting forward problem, requirement analysis, model design, system design and system implementation, the thesis puts forward, designs and implements an electric vehicle orderly charging monitoring system based on cloud computing platform.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491.8;TP277

【引证文献】