本文選題：廣域量測(cè)　切入點(diǎn)：大數(shù)據(jù)　出處：《電網(wǎng)技術(shù)》2017年01期 　論文類型：期刊論文

【摘要】：為深入理解廣域量測(cè)信息特征,采用類比分析方法探究了廣域量測(cè)理論研究成果難以轉(zhuǎn)換成實(shí)際應(yīng)用的原因。首先,以信息論大數(shù)據(jù)4V特征為條件,提出一種判斷大數(shù)據(jù)的邏輯結(jié)構(gòu)。然后,深入分析電網(wǎng)廣域信息暫態(tài)數(shù)據(jù)、動(dòng)態(tài)數(shù)據(jù)及事件標(biāo)識(shí)數(shù)據(jù)的產(chǎn)生過(guò)程、描述結(jié)構(gòu)及關(guān)聯(lián)關(guān)系,結(jié)合某省WAMS系統(tǒng)實(shí)例,與大數(shù)據(jù)判斷條件進(jìn)行逐一類比分析,論述了廣域量測(cè)信息是一種電網(wǎng)特有的大數(shù)據(jù),難以滿足多數(shù)WAMS理論研究成果對(duì)于數(shù)據(jù)持續(xù)性和準(zhǔn)確性的要求,是理論成果難以向?qū)嵱棉D(zhuǎn)換的重要原因。實(shí)現(xiàn)WAMS理論成果實(shí)用化,必須有效處理廣域信息大數(shù)據(jù),由此提出了建立數(shù)據(jù)可信分級(jí)、設(shè)計(jì)專用數(shù)據(jù)處理控制器、增添數(shù)據(jù)分群管理模式等數(shù)據(jù)應(yīng)用策略。
[Abstract]:In order to deeply understand the characteristics of wide-area measurement information, the reason why the research results of wide-area measurement theory is difficult to be converted into practical application is explored by analogy analysis. First, the information theory big data 4V feature is used as a condition. A logic structure for judging big data is proposed. Then, the generation process of power grid wide area information transient data, dynamic data and event identification data is analyzed in depth, and the structure and correlation relationship are described. A provincial WAMS system example is given. By analogy analysis with big data, this paper discusses that wide-area measurement information is a kind of special power grid big data, which is difficult to meet the requirements of data continuity and accuracy of most WAMS theoretical research results. To realize the practicability of WAMS theory, big data must deal with wide-area information effectively. Therefore, it is proposed to establish data credible grading and design special data processing controller. Add data cluster management model and other data application strategies.
【作者單位】： 中國(guó)農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院;中國(guó)電力科學(xué)研究院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51207143) 國(guó)家電網(wǎng)公司科技項(xiàng)目(XT71-15-056)~~
【分類號(hào)】：TM76

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本文編號(hào)：1620540