【摘要】：穩(wěn)定而優(yōu)質(zhì)的電能是當(dāng)今社會(huì)科學(xué)技術(shù)發(fā)展、國民經(jīng)濟(jì)飛躍的主要驅(qū)動(dòng)力。為了保障電力系統(tǒng)可以安全、可靠地運(yùn)行,必須進(jìn)行電能質(zhì)量的管理工作。電能質(zhì)量管理的前提是可以準(zhǔn)確地評估電能質(zhì)量、查找電能質(zhì)量存在的問題,它可以為管理電能質(zhì)量提出科學(xué)依據(jù)與實(shí)際數(shù)據(jù)支持。電能質(zhì)量的評估又依賴于電力系統(tǒng)所產(chǎn)生、采集和統(tǒng)計(jì)到的大量數(shù)據(jù),這些數(shù)據(jù)中可能存在各種各樣的問題與雜質(zhì),只有利用數(shù)據(jù)清洗技術(shù),去除雜質(zhì)與錯(cuò)誤,才有可能提高電能質(zhì)量評估的效率及電能質(zhì)量管理的水平。本文首先對數(shù)據(jù)清洗技術(shù)的主要內(nèi)容進(jìn)行研究。采用“局部切比雪夫定理”與“鄰近數(shù)據(jù)平均值法”針對屬性值的錯(cuò)誤進(jìn)行清洗,利用“排序鄰居算法”清洗重復(fù)數(shù)據(jù),最終得到相對較為合理的統(tǒng)計(jì)數(shù)據(jù)。其次研究了電能質(zhì)量的含義及其性質(zhì),并重點(diǎn)研究了構(gòu)建評估體系的指標(biāo)含義及計(jì)算公式。再次研究了熵權(quán)法、變異系數(shù)法、層次分析法這三種客觀主觀權(quán)重法,確定了評估指標(biāo)的權(quán)重及評估結(jié)果。為了彌補(bǔ)和修正客觀主觀賦權(quán)法所自有的片面性與不合理性,又采用灰靶理論、基于粗糙集和信息熵的方法、最小二乘法得到綜合權(quán)重及評估結(jié)果。之后又采用平均值法、Copeland法、模糊Borda法對上述評估結(jié)果進(jìn)行組合評價(jià),最終得到最全面的評估結(jié)果。最后利用編碼等方式針對某110kV監(jiān)測點(diǎn)實(shí)現(xiàn)了數(shù)據(jù)清洗與電能質(zhì)量的評估。本文涉及的六種賦權(quán)方法,三種組合評價(jià)方法可以強(qiáng)有力地得到最為準(zhǔn)確的電能質(zhì)量評估結(jié)果,對提升評估效率與準(zhǔn)確性做出了貢獻(xiàn),具有較強(qiáng)的推廣價(jià)值。
[Abstract]:Stable and high-quality electric energy is the main driving force of the development of science and technology and the leap of national economy. In order to ensure the safe and reliable operation of power system, power quality management must be carried out. The premise of power quality management is to accurately evaluate power quality and find out the existing problems of power quality. It can provide scientific basis and practical data support for power quality management. The evaluation of power quality depends on the large amount of data generated, collected and counted by the power system. There may be a variety of problems and impurities in these data, only by using data cleaning technology, the impurities and errors can be removed. It is possible to improve the efficiency of power quality assessment and the level of power quality management. In this paper, the main content of data cleaning technology is studied. The method of "local Chebyshev theorem" and "the average value of adjacent data" is used to clean the error of attribute value, and the "ranking neighbor algorithm" is used to clean the repeated data, and a relatively reasonable statistical data is obtained. Secondly, the meaning and properties of power quality are studied, and the index meaning and calculation formula of constructing evaluation system are studied. Three objective subjective weight methods, entropy weight method, coefficient of variation method and analytic hierarchy process method, are studied again to determine the weight of the evaluation index and the evaluation results. In order to remedy and correct the one-sidedness and irrationality of the objective subjective weighting method, the grey target theory and the method of rough set and information entropy are used to obtain the comprehensive weight and evaluation results by the least square method. Then the method of average value and fuzzy Borda method are used to evaluate the above evaluation results, and finally the most comprehensive evaluation results are obtained. Finally, data cleaning and power quality evaluation are realized for a certain 110kV monitoring point by coding and so on. The six weighting methods and the three combined evaluation methods can obtain the most accurate results of power quality evaluation, and contribute to the improvement of evaluation efficiency and accuracy.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM732;TP311.13

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