基于云计算的充电站充电负荷预测体系结构研究

发布时间：2018-05-29 14:23

本文选题：充电站 + 智能电网　；参考：《华北电力大学》2015年硕士论文

【摘要】：发展低碳经济是我国经济发展的主旋律,作为新能源战略和智能电网重要组成部分的电动汽车,今后将成为中国能源产业和汽车_工业发展的重点。电动汽车作为国务院确定的战略性新兴产业之一,未来五年将是研发与产业化的好机遇。电动汽车的规模化发展,充电设施的规模化建设,用电设备的规模化增加,大量的充电负荷接入电网,刈。电力系统的规划、运行以及电力市场的运营均会产生深刻的影响。面对电动汽车、充电设施、用电设备的规模化增加,企业所需面对的用户和数据也日益剧增,数据的并发访问、数据存储和管理的压力大大增加,因此引入云计算技术。云计算是一种基于互联网的计算方式,它有概然性、弥漫性、同时性等诸多优越的特性,它把一切都拿到网络上,通过网络把物理上分散的资源连接起来处理问题。电动汽车的产业化规模化发展,充电负荷将给电网运行带来很大挑战,电动汽车用户、充电设施分布在全国各地,数据采集和存储都需要统一的平台,才能进行准确的负荷预测,伴随着云时代的来临,建立一套基于网络基础的充电站充电负荷预测体系,对于电动汽车长远发展有着很重要的理论意义和实际意义。如何准确的进行充电负荷控制,更好的调整充电策略,利用云计算、云存储、大数据等计算机前沿科技进行体系研究,保证预测的及时性、准确性、完整性,实现优化资源的利用,最大程度实现数据资源共享,对我们提出了新的挑战。本文通过对中国电网发展的初步探索,从电动汽车充电模式、电池特性、电动汽车发展预测等方面研究了影响充电负荷的各种因素,分析了云计算的特点、体系构架、技术关键和数据中心特点；建立了基于云计算的智能电网网络结构,讨论了云计算结构网络考虑时空分布电动汽车充电负荷预测,从云计算出发建立电网结构,研究如何利用云计算进行充电站充电负荷预测体系的大数据分析。
[Abstract]:The development of low-carbon economy is the main theme of China's economic development. As an important part of new energy strategy and smart grid, electric vehicles will become the focus of the development of energy industry and automobile industry in China in the future. Electric vehicle, as one of the strategic emerging industries determined by the State Council, will be a good opportunity for R & D and industrialization in the next five years. The development of electric vehicles, the construction of charging facilities, the increase of the scale of electric equipment, a large number of charging load connected to the power grid. Power system planning, operation and electricity market operation will have a profound impact. In the face of the increasing scale of electric vehicles, charging facilities and electric equipment, the users and data that enterprises have to face are also increasing rapidly. The pressure of concurrent access of data, data storage and management is greatly increased, so cloud computing technology is introduced. Cloud computing is a kind of computing method based on the Internet. It has many advantages, such as generality, diffusing, and simultaneous. It takes everything to the network and connects the physically dispersed resources to deal with the problem through the network. The large-scale development of electric vehicle industrialization and charging load will bring great challenges to the operation of electric network. Electric vehicle users and charging facilities are distributed all over the country. Data collection and storage all need a unified platform. With the advent of the cloud age, it is of great theoretical and practical significance to establish a charging load forecasting system based on network for the long-term development of electric vehicles. How to accurately control charge load, better adjust charging strategy, make use of cloud computing, cloud storage, big data and other advanced computer science and technology for system research, to ensure the timeliness, accuracy and integrity of prediction, It is a new challenge for us to optimize the utilization of resources and to share data resources to the greatest extent. Based on the preliminary exploration of the development of China's power grid, this paper studies various factors that affect the charging load from the aspects of electric vehicle charging mode, battery characteristics and electric vehicle development prediction, and analyzes the characteristics and architecture of cloud computing. Based on cloud computing, the smart grid network structure is established, and the cloud computing network structure considering space-time distribution electric vehicle charging load forecasting is discussed, and the grid structure is established from cloud computing. This paper studies how to use cloud computing to analyze charging load forecasting system based on big data.
【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】：TM715

【参考文献】