本文選題：充電站 + 智能電網(wǎng)　； 參考：《華北電力大學(xué)》2015年碩士論文

【摘要】：發(fā)展低碳經(jīng)濟是我國經(jīng)濟發(fā)展的主旋律,作為新能源戰(zhàn)略和智能電網(wǎng)重要組成部分的電動汽車,今后將成為中國能源產(chǎn)業(yè)和汽車_工業(yè)發(fā)展的重點。電動汽車作為國務(wù)院確定的戰(zhàn)略性新興產(chǎn)業(yè)之一,未來五年將是研發(fā)與產(chǎn)業(yè)化的好機遇。電動汽車的規(guī)模化發(fā)展,充電設(shè)施的規(guī)�；ㄔO(shè),用電設(shè)備的規(guī)�；黾�,大量的充電負(fù)荷接入電網(wǎng),刈。電力系統(tǒng)的規(guī)劃、運行以及電力市場的運營均會產(chǎn)生深刻的影響。面對電動汽車、充電設(shè)施、用電設(shè)備的規(guī)�；黾�,企業(yè)所需面對的用戶和數(shù)據(jù)也日益劇增,數(shù)據(jù)的并發(fā)訪問、數(shù)據(jù)存儲和管理的壓力大大增加,因此引入云計算技術(shù)。云計算是一種基于互聯(lián)網(wǎng)的計算方式,它有概然性、彌漫性、同時性等諸多優(yōu)越的特性,它把一切都拿到網(wǎng)絡(luò)上,通過網(wǎng)絡(luò)把物理上分散的資源連接起來處理問題。電動汽車的產(chǎn)業(yè)化規(guī)�；l(fā)展,充電負(fù)荷將給電網(wǎng)運行帶來很大挑戰(zhàn),電動汽車用戶、充電設(shè)施分布在全國各地,數(shù)據(jù)采集和存儲都需要統(tǒng)一的平臺,才能進行準(zhǔn)確的負(fù)荷預(yù)測,伴隨著云時代的來臨,建立一套基于網(wǎng)絡(luò)基礎(chǔ)的充電站充電負(fù)荷預(yù)測體系,對于電動汽車長遠(yuǎn)發(fā)展有著很重要的理論意義和實際意義。如何準(zhǔn)確的進行充電負(fù)荷控制,更好的調(diào)整充電策略,利用云計算、云存儲、大數(shù)據(jù)等計算機前沿科技進行體系研究,保證預(yù)測的及時性、準(zhǔn)確性、完整性,實現(xiàn)優(yōu)化資源的利用,最大程度實現(xiàn)數(shù)據(jù)資源共享,對我們提出了新的挑戰(zhàn)。本文通過對中國電網(wǎng)發(fā)展的初步探索,從電動汽車充電模式、電池特性、電動汽車發(fā)展預(yù)測等方面研究了影響充電負(fù)荷的各種因素,分析了云計算的特點、體系構(gòu)架、技術(shù)關(guān)鍵和數(shù)據(jù)中心特點；建立了基于云計算的智能電網(wǎng)網(wǎng)絡(luò)結(jié)構(gòu),討論了云計算結(jié)構(gòu)網(wǎng)絡(luò)考慮時空分布電動汽車充電負(fù)荷預(yù)測,從云計算出發(fā)建立電網(wǎng)結(jié)構(gòu),研究如何利用云計算進行充電站充電負(fù)荷預(yù)測體系的大數(shù)據(jù)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.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TM715

【參考文獻】

相關(guān)期刊論文 前4條

1 周國亮;王桂蘭;葛佳;劉治安;孫玉寶;;基于云計算的用戶側(cè)短期用電負(fù)荷預(yù)測技術(shù)[J];電力信息化;2012年03期

2 陳全;鄧倩妮;;云計算及其關(guān)鍵技術(shù)[J];計算機應(yīng)用;2009年09期

3 吳奎華;孫偉;張曉磊;汪nr;楊波;朱毅;;電動汽車充電負(fù)荷建模及其對電網(wǎng)負(fù)荷特性的影響[J];山東電力技術(shù);2013年05期

4 喬弘;吳蓉;;智能電網(wǎng)的特點與發(fā)展淺述[J];中國新技術(shù)新產(chǎn)品;2010年19期

，

本文編號：1951199