【摘要】：本文針對(duì)電壓暫降特性及嚴(yán)重程度綜合評(píng)估展開(kāi)研究。在電壓暫降特性研究方面,以我國(guó)四個(gè)大型城市電網(wǎng)電能質(zhì)量監(jiān)測(cè)系統(tǒng)中電壓暫降實(shí)測(cè)數(shù)據(jù)為基礎(chǔ),從典型波形、統(tǒng)計(jì)表格、累計(jì)概率、暫降相序四個(gè)方面對(duì)暫降事件進(jìn)行分類統(tǒng)計(jì)。通過(guò)對(duì)典型波形的分類統(tǒng)計(jì),分析電壓暫降的描述特性;依據(jù)統(tǒng)計(jì)表格、累計(jì)概率曲線與暫降相序的統(tǒng)計(jì)結(jié)果分析暫降事件的分布特性,并給出了相關(guān)結(jié)論。在電壓暫降嚴(yán)重程度評(píng)估方面,為克服現(xiàn)有評(píng)估指標(biāo)的不足,針對(duì)不同的電壓暫降評(píng)估需求,本文提出了兩種評(píng)估方法:1)提出了基于一種新型描述的電壓暫降嚴(yán)重程度綜合評(píng)估方法,該方法適用于單次事件、節(jié)點(diǎn)及系統(tǒng)電壓暫降的精確評(píng)估�；贗EC61000-2-8統(tǒng)計(jì)表格確定評(píng)價(jià)指標(biāo)及等級(jí)劃分;提出了影響度的概念,通過(guò)熵權(quán)法將層次分析法與權(quán)值函數(shù)法計(jì)算的各特征量影響度值相結(jié)合;采用多暫降閾值和持續(xù)時(shí)間序列的電壓暫降新型描述方法與標(biāo)準(zhǔn)化模值計(jì)算方式定義了相關(guān)的綜合影響度指標(biāo)。其特點(diǎn)為利用熵權(quán)法將層次分析法與權(quán)值函數(shù)法相結(jié)合,綜合考慮了主、客觀性,采用新型描述方法更加準(zhǔn)確地反映了電壓暫降實(shí)際波形特征,令評(píng)估結(jié)果更加準(zhǔn)確。2)提出了一種基于組合賦權(quán)與TOPSIS模型的電壓暫降嚴(yán)重程度綜合評(píng)估方法,該方法適用于多個(gè)節(jié)點(diǎn)或系統(tǒng)間暫降嚴(yán)重性的整體評(píng)比。以SARFI指標(biāo)、平均暫降能量指標(biāo)與暫降嚴(yán)重性指標(biāo)為元素建立屬性集合。采用熵權(quán)法與變異系數(shù)法計(jì)算各指標(biāo)組合權(quán)值,計(jì)算各評(píng)估對(duì)象與模型中正理想解的加權(quán)距離及相對(duì)近似度,并據(jù)此判斷暫降嚴(yán)重程度。該方法的特點(diǎn)是將三個(gè)典型評(píng)估指標(biāo)綜合考慮,保證了評(píng)估結(jié)果的正確性,組合權(quán)值既從整體又從局部反映了各指標(biāo)相對(duì)重要程度,TOPSIS模型原理簡(jiǎn)單,易于實(shí)現(xiàn),評(píng)估結(jié)果具有相對(duì)性。依托某城市電網(wǎng)電壓暫降監(jiān)測(cè)數(shù)據(jù),對(duì)上述兩種方法進(jìn)行實(shí)例分析,通過(guò)與現(xiàn)有典型指標(biāo)評(píng)估結(jié)果的對(duì)比分析,驗(yàn)證了所提出兩種方法的正確性。
[Abstract]:In this paper, the comprehensive evaluation of voltage sag characteristics and severity is studied. In the study of voltage sag characteristics, based on the measured data of voltage sag in power quality monitoring systems of four large cities in China, the sag events are classified and counted from four aspects: typical waveform, statistical table, cumulative probability and sag phase sequence. Through the classification and statistics of typical waveforms, the description characteristics of voltage sag are analyzed, and the distribution characteristics of sag events are analyzed according to the statistical results of cumulative probability curve and sag phase sequence, and the related conclusions are given. In order to overcome the shortcomings of the existing evaluation indexes, two evaluation methods are proposed in this paper: 1) based on a new description, a comprehensive evaluation method of voltage sag severity is proposed, which is suitable for the accurate evaluation of single event, node and system voltage sag. Based on IEC61000-2-8 statistical table, the evaluation index and grade classification are determined, the concept of influence degree is put forward, the influence value of each characteristic quantity calculated by analytic hierarchy process (AHP) and weight function method is combined by entropy weight method, and the related comprehensive influence index is defined by using the new description method of voltage sag of multiple sag threshold and duration time series and the standardized modulus calculation method. Its characteristics are that the analytic hierarchy process (AHP) and the weight function method are combined by entropy weight method, and the main and objective are considered synthetically, and the new description method is used to reflect the actual waveform characteristics of voltage sag more accurately, which makes the evaluation result more accurate. 2) A comprehensive evaluation method of voltage sag severity based on combination weighting and TOPSIS model is proposed, which is suitable for the overall evaluation of sag severity between multiple nodes or systems. Taking SARFI index, average sag energy index and sag severity index as elements, the attribute set is established. Entropy weight method and coefficient of variation method are used to calculate the combined weights of each index, and the weighted distance and relative similarity between each evaluation object and the positive ideal solution in the model are calculated, and the severity of sag is judged. The characteristic of this method is that the three typical evaluation indexes are considered comprehensively to ensure the correctness of the evaluation results, and the combined weights reflect the relative importance of each index both as a whole and locally. The principle of TOPSIS model is simple and easy to realize, and the evaluation results are relative. Based on the monitoring data of voltage sag in a city power grid, the above two methods are analyzed by examples, and the correctness of the two methods is verified by comparing with the evaluation results of the existing typical indexes.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM714.2

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本文編號(hào)：2507202