本文選題：電力系統(tǒng) + 輸電線路��； 參考：《安徽理工大學(xué)》2017年碩士論文

【摘要】：輸電線路的安全穩(wěn)定對電力系統(tǒng)可靠運行至關(guān)重要,隨著電力系統(tǒng)向智能化、復(fù)雜化方向發(fā)展,輸電線路的故障診斷與健康管理正逐步受到重視。輸電線以及配電線在電網(wǎng)中遍布在系統(tǒng)的每個角落并處于露天的狀況下,故障發(fā)生率相比其他電氣設(shè)備高很多,因而傳統(tǒng)的人工巡線方式查找故障類型已無法滿足當(dāng)前電力系統(tǒng)發(fā)展的要求。因此,基于輸電線路狀態(tài)信號的快速、可靠的輸電線路故障分析方法對電力系統(tǒng)的安全穩(wěn)定運行及科學(xué)健康管理具有重要的意義。輸電線路發(fā)生故障時,故障信息隱含于故障信號中,可通過適當(dāng)?shù)墓收闲盘柗治龇椒ㄒ詫崿F(xiàn)其有效診斷�，F(xiàn)有電力系統(tǒng)故障信號分析方法種類繁多,其中傅里葉變換、小波變換、經(jīng)驗?zāi)B(tài)分解等應(yīng)用最為廣泛。傅里葉變換在分析線性信號的全局性具有良好的優(yōu)勢,但不能有效的給出非線性信號的局部特征信息。小波分析具有對被分析故障信號可進(jìn)行任意的放大平移并對其特征進(jìn)行提取的優(yōu)點,但該方法存在選取不同小波基和分解尺度造成故障信號特征的遺失及分析故障信號無法反映信號的本質(zhì)特征的缺點。經(jīng)驗?zāi)B(tài)分解一種新的信號分析方法,它克服小波分析的缺點,自動地選擇最佳基函數(shù)對信號進(jìn)行分解,確定信號在不同頻帶的分辨率,避免了選取小波基與分解尺度的困難。但該方法屬于遞歸式模態(tài)分解易出現(xiàn)模態(tài)混疊造成某個分量頻帶過寬、噪聲干擾過多而掩蓋故障信號微弱的特征信息。由于輸電線路發(fā)生故障時,其故障波形因時間、故障點、故障過渡電阻及系統(tǒng)工作情況的不同而有所差異,具有突變性及隨機(jī)性,在故障信號中含有大量的非周期性分量和大量的諧波并且這些分量隨著時間會逐漸衰減,因此在上述三種傳統(tǒng)方法分析輸電線路故障信號時,會遺失信號的部分有效特征信息,并影響最終的故障診斷結(jié)果。本文鑒于以上原因,提出基于變分模態(tài)分解和排列熵結(jié)合的方法來診斷輸電線路故障,以此解決上述存在的問題。本文輸電線路故障診斷主要步驟分為:第一步驟,利用小波變換與排列熵的方案對輸電線路故障進(jìn)行處理分析;第二步驟,利用變分模態(tài)分解與排列熵的方案對輸電線路故障進(jìn)行處理分析。最后將兩種方案的最終結(jié)果進(jìn)行比較。針對上述算法,本文采用PSCAD和MATLAB對算法進(jìn)行仿真。
[Abstract]:The safety and stability of transmission line is very important to the reliable operation of power system. With the development of intelligent and complicated power system, fault diagnosis and health management of transmission line are being paid more and more attention. Transmission lines and distribution lines are scattered throughout the system and in open air conditions, and the incidence of failures is much higher than that of other electrical equipment. Therefore, the traditional manual inspection method can not meet the requirements of the current power system development. Therefore, the fast and reliable fault analysis method based on the transmission line state signal is of great significance to the safe and stable operation and scientific health management of power system. The fault information is hidden in the fault signal when the fault occurs in the transmission line, and it can be effectively diagnosed by the appropriate fault signal analysis method. There are many kinds of power system fault signal analysis methods, among which Fourier transform, wavelet transform and empirical mode decomposition are the most widely used. Fourier transform has a good advantage in analyzing the global character of linear signal, but it can not give the local characteristic information of nonlinear signal effectively. Wavelet analysis has the advantages of arbitrary amplification and translation of the analyzed fault signal and extraction of its features. However, this method has the disadvantage of selecting different wavelet bases and decomposing scale, which results in the loss of fault signal features and the analysis of fault signal can not reflect the essential characteristics of the signal. Empirical mode decomposition (EMD) is a new signal analysis method, which overcomes the shortcoming of wavelet analysis, automatically selects the best basis function to decompose the signal, determines the resolution of the signal in different frequency bands, and avoids the difficulty of selecting wavelet basis and decomposition scale. But this method belongs to the recursive mode decomposition, which is prone to appear mode aliasing, which leads to a component frequency band too wide, too much noise interference, and masking the weak characteristic information of the fault signal. Because the fault waveform of transmission line is different because of different time, fault point, fault transition resistance and system working condition, it has the character of mutation and randomness. There are a lot of aperiodic components and lots of harmonics in the fault signal and these components will attenuate gradually with time. Therefore, some effective characteristic information of the transmission line fault signal will be lost when the three traditional methods mentioned above are used to analyze the fault signal. And affect the final fault diagnosis results. In view of the above reasons, a method based on variational mode decomposition and permutation entropy is proposed to diagnose the fault of transmission lines and solve the problems mentioned above. In this paper, the main steps of transmission line fault diagnosis are as follows: the first step, using wavelet transform and permutation entropy to deal with the transmission line fault, the second step, The scheme of variational mode decomposition and permutation entropy is used to deal with transmission line faults. Finally, the final results of the two schemes are compared. In this paper, PSCAD and MATLAB are used to simulate the algorithm.
【學(xué)位授予單位】：安徽理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM755

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