本文選題：電能質(zhì)量監(jiān)測系統(tǒng) + MongoDB��； 參考：《華中科技大學》2015年碩士論文

【摘要】：縣級電能質(zhì)量監(jiān)測系統(tǒng)作為電能質(zhì)量監(jiān)測體系的重要基礎(chǔ),監(jiān)測節(jié)點眾多,采集數(shù)據(jù)量大。隨著監(jiān)測節(jié)點和數(shù)據(jù)的不斷增加,電能質(zhì)量數(shù)據(jù)呈現(xiàn)海量化趨勢,使得縣級電能質(zhì)量監(jiān)測系統(tǒng)面臨著很大的性能壓力,系統(tǒng)的擴展成本和人力成本也會急劇攀升�？h供電公司由于自身條件的限制,能夠投入的資源有限,因此,充分利用已有資源,構(gòu)建一套高效存儲與快速處理海量數(shù)據(jù)的電能質(zhì)量監(jiān)測系統(tǒng),對于縣級供電企業(yè)來說具有重要的實際意義。本文重點研究了縣級電能質(zhì)量監(jiān)測系統(tǒng)中的數(shù)據(jù)存儲與解析問題。首先通過研究國內(nèi)外電能質(zhì)量監(jiān)測系統(tǒng)和NoSQL數(shù)據(jù)庫的發(fā)展現(xiàn)狀,指出了MongoDB數(shù)據(jù)庫在應(yīng)對海量電能質(zhì)量數(shù)據(jù)上的優(yōu)勢。接著通過對縣級電能質(zhì)量監(jiān)測系統(tǒng)進行需求分析,明確了系統(tǒng)中的兩個關(guān)鍵問題,即海量電能質(zhì)量數(shù)據(jù)的存儲與解析。然后設(shè)計并實現(xiàn)了基于MongoDB的海量電能質(zhì)量數(shù)據(jù)存儲方案,并實現(xiàn)了一套數(shù)據(jù)接口。接著在分析已有電能質(zhì)量數(shù)據(jù)解析方案不足的基礎(chǔ)上,結(jié)合Hadoop MapReduce并行框架設(shè)計并實現(xiàn)了適合縣級電能質(zhì)量監(jiān)測系統(tǒng)的海量數(shù)據(jù)快速解析方案。最后為了驗證存儲方案和解析方案以及綜合方案的性能,對存儲方案的數(shù)據(jù)寫入和查詢性能、解析方案的數(shù)據(jù)解析性能以及綜合方案的性能進行了測試和分析。測試結(jié)果表明,本文提出的方案,相對基于關(guān)系型數(shù)據(jù)庫的存儲方案,具有更好的數(shù)據(jù)存儲和查詢性能,和傳統(tǒng)解析方案以及已有的并行解析方案相比,具有更高的解析效率。
[Abstract]:As an important basis of the power quality monitoring system, the county power quality monitoring system is an important basis for the monitoring system of power quality. There are numerous monitoring nodes and large amount of data collection. With the continuous increase of monitoring nodes and data, the power quality data presents a huge trend, which makes the county power quality monitoring system face great performance pressure, the expansion cost of the system and human resources. Therefore, the county power supply company has limited resources due to its own conditions. Therefore, making full use of the existing resources to build a set of efficient storage and rapid processing of mass data power quality monitoring system for the county power supply enterprises is of great importance. This paper focuses on the county power quality. The problem of data storage and analysis in the quantity monitoring system. First, by studying the development status of power quality monitoring system and NoSQL database at home and abroad, this paper points out the advantages of MongoDB database in dealing with mass data of power quality. Then, by analyzing the demand of the county power quality monitoring system, two key points in the system are clearly defined. The key problem is the storage and analysis of mass power quality data. Then, a data storage scheme based on MongoDB is designed and implemented, and a set of data interface is realized. Then, on the basis of analyzing the deficiencies of the existing power quality data analysis scheme, it is designed and implemented at the county level with the Hadoop MapReduce parallel framework. In order to verify the storage scheme and the performance of the solution and the comprehensive scheme, the data write and query performance of the storage scheme, the performance of the data analysis and the performance of the comprehensive scheme are tested and analyzed. The case, which is relatively based on the relational database, has better data storage and query performance. Compared with the traditional parsing scheme and the existing parallel solutions, it has higher resolution efficiency.

【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM76

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