基于多网融合的电动汽车有序充电管理系统的研究

发布时间：2018-11-10 17:08

【摘要】：工业革命以后,人类社会不断进步,全球经济飞速发展,化石能源的使用在提高人类生活水平的同时,也带来了严重的环境污染和能源短缺问题,而这些问题正逐渐成为影响人类长远生存的重要因素。电动汽车的出现,为以上问题提供了一种新的解决方案,得到全球各国政府大力支持,但是,大规模电动汽车作为用电负荷接入电网给电网的安全稳定运行带来了巨大的压力和挑战。本课题提出了一种基于多信息网络的电动汽车有序充电模型,该模型兼顾电动汽车车联网、智能电网以及充电设备物联网三方面因素,从电网负荷预测出发综合考虑充电用户历史行为习惯和充电设备的历史使用情况,实现充电汽车有序充电。同时,该模型还最大限度地保证了电网侧安全稳定运行和充电用户及时方便充电的使用需求,并且根据分析得出充电设备运营策略的优劣,为充电设备运营商调整运营方案进一步优化区域有序充电服务提供了依据。基于多网的有序充电管理系统是在车联网、智能电网和物联网多网数据融合的前提下实现的。随着电动汽车行业整体的进步与发展,相应的配套网络也在飞速完善,因此产生了海量的、异构化的基础数据,这些数据集中在不同服务运营商的信息系统中,彼此不能互融,为整体分析三网数据带来了不可逾越的物理隔离。因此本课题首先构建了基于REST(Representational State Transfer)的Web Service数据服务接口,利用REST轻便高效的数据交互方案,实现了三网数据在数据层级别的融合。然后,利用融合后的基础数据,完成对充电用户行为习惯和充电设备使用热度的分析处理,实现了多网络数据在特征层和决策层进一步融合,提出由电网侧发起的主动调峰有序充电策略。最终完成了系统的实现以及在云服务平台上的部署工作。
[Abstract]:After the industrial revolution, human society continued to progress and the global economy developed rapidly. The use of fossil energy not only improved the living standards of human beings, but also brought serious environmental pollution and energy shortage problems. These problems are gradually becoming an important factor affecting the long-term survival of human beings. The emergence of electric vehicles provides a new solution to these problems, with strong support from governments around the world, but, Large-scale electric vehicles (EVs), which are connected to the power grid as electric load, bring great pressure and challenge to the safe and stable operation of the grid. In this paper, an ordered charging model for electric vehicles based on multi-information network is proposed. The model takes into account three factors: the network of electric vehicles, the smart grid and the Internet of things of charging equipment. Considering the historical behavior of charging users and the historical usage of charging equipment, the orderly charging of charging vehicles can be realized based on the load forecasting of power grid. At the same time, the model can ensure the safe and stable operation of the power grid side and the timely and convenient charging requirements of the charging users, and according to the analysis, the advantages and disadvantages of the charging equipment operation strategy are obtained. It provides the basis for the operators to adjust the operation plan and further optimize the regional orderly charging service. The orderly charging management system based on multi-network is implemented under the premise of data fusion of car network, smart grid and Internet of things. With the progress and development of the electric vehicle industry as a whole, the corresponding supporting network is also improving rapidly, so it produces massive, isomerization basic data, which are concentrated in the information systems of different service operators, so they can't melt each other. For the overall analysis of the three networks of data brings an insurmountable physical isolation. Therefore, this paper first constructs the Web Service data service interface based on REST (Representational State Transfer), and realizes the integration of the three-network data at the data layer level by using the REST portable and efficient data exchange scheme. Then, by using the integrated basic data, the behavior habits of charging users and the heat intensity of charging equipment are analyzed and processed, and the multi-network data is further fused in the feature layer and decision layer. An active peak-shaving orderly charging strategy initiated by the grid side is proposed. Finally, the system is implemented and deployed on the cloud service platform.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.8;TP315

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