本文選題：電動(dòng)汽車(chē) + 區(qū)域電網(wǎng)�。� 參考：《華北電力大學(xué)》2015年碩士論文

【摘要】：經(jīng)濟(jì)的增長(zhǎng)和社會(huì)的進(jìn)步,帶動(dòng)人們生活水平提高的同時(shí),也造成了深刻的能源環(huán)境問(wèn)題,能源短缺和環(huán)境污染是當(dāng)前人類(lèi)社會(huì)面臨的重大問(wèn)題。電動(dòng)汽車(chē)的產(chǎn)生和發(fā)展,為人類(lèi)解決能源環(huán)境問(wèn)題提供了新的思路。然而,大規(guī)模電動(dòng)汽車(chē)的投入運(yùn)行與接入電網(wǎng),對(duì)城市交通、電網(wǎng)安全穩(wěn)定等是一個(gè)重大挑戰(zhàn)。本課題提出一種綜合考慮電網(wǎng)側(cè)電網(wǎng)負(fù)荷、充電公平性和用戶側(cè)便利性、快捷性等因素的多目標(biāo)優(yōu)化充電模型,依此模型對(duì)區(qū)域電網(wǎng)內(nèi)電動(dòng)汽車(chē)進(jìn)行有序充電,在保證公平性的基礎(chǔ)上,實(shí)現(xiàn)最優(yōu)化有序充電,盡可能保證電網(wǎng)安全穩(wěn)定運(yùn)行、提升用戶體驗(yàn)和節(jié)約成本。運(yùn)用迭代法、貪心法、優(yōu)先級(jí)法和多級(jí)反饋隊(duì)列等經(jīng)典算法,解決多目標(biāo)優(yōu)化模型的最優(yōu)解問(wèn)題。區(qū)域電網(wǎng)電動(dòng)汽車(chē)多目標(biāo)優(yōu)化充電模型的實(shí)現(xiàn)需要電力網(wǎng)、車(chē)聯(lián)網(wǎng)、充電站(樁)聯(lián)網(wǎng)及其他相關(guān)信息的融合。隨著行業(yè)的發(fā)展,在多信息源融合的過(guò)程中,會(huì)產(chǎn)生海量異構(gòu)化數(shù)據(jù),呈大數(shù)據(jù)化,采用傳統(tǒng)的單機(jī)串行化處理模式已經(jīng)無(wú)法滿足時(shí)間和空間上的需求,其存儲(chǔ)和計(jì)算都將成為瓶頸。因此,本課題提出并實(shí)現(xiàn)了基于云計(jì)算平臺(tái)的電動(dòng)汽車(chē)有序充電監(jiān)控系統(tǒng)。利用Hadoop開(kāi)源云計(jì)算平臺(tái),組建計(jì)算集群,實(shí)現(xiàn)此類(lèi)大數(shù)據(jù)的并行化處理。系統(tǒng)以多目標(biāo)優(yōu)化充電模型為核心,設(shè)計(jì)系統(tǒng)功能,包括數(shù)據(jù)接收、數(shù)據(jù)實(shí)時(shí)與離線處理、數(shù)據(jù)展示等。設(shè)計(jì)系統(tǒng)物理和邏輯框架,依此框架搭建Hadoop云計(jì)算平臺(tái),利用HBase分布式數(shù)據(jù)庫(kù)存儲(chǔ)電網(wǎng)側(cè)和用戶側(cè)數(shù)據(jù),利用MapReduce編程框架實(shí)現(xiàn)基礎(chǔ)性算法,并實(shí)現(xiàn)系統(tǒng)功能。課題按照提出問(wèn)題-需求分析-模型設(shè)計(jì)-系統(tǒng)設(shè)計(jì)-系統(tǒng)實(shí)現(xiàn)的順序逐步深入進(jìn)行研究,提出、設(shè)計(jì)并實(shí)現(xiàn)基于云計(jì)算平臺(tái)的電動(dòng)汽車(chē)有序充電監(jiān)控系統(tǒng)。
[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.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U491.8;TP277

【引證文獻(xiàn)】

相關(guān)會(huì)議論文 前1條

1 李杰;王愛(ài)民;于金剛;;智能電網(wǎng)中云計(jì)算技術(shù)的應(yīng)用研究[A];中國(guó)智能電網(wǎng)學(xué)術(shù)研討會(huì)論文集[C];2011年

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本文編號(hào)：1776609