【摘要】：隨著電網(wǎng)規(guī)模的不斷擴大、輸送容量和電壓等級的不斷提高，電力系統(tǒng)過電壓對輸電線路和電氣設(shè)備絕緣造成的危害越來越嚴重，因此研究電力系統(tǒng)過電壓是保障電網(wǎng)安全可靠運行的重要課題。電力系統(tǒng)過電壓種類較多，各類型過電壓的產(chǎn)生機理不同，防護措施也不盡相同。實時監(jiān)測電力系統(tǒng)出現(xiàn)的各種過電壓信號，快速準(zhǔn)確的判別故障類型，對處理故障和改善絕緣配合是十分必要的。 本文分別對輸電線路雷電過電壓與變電站過電壓進行了研究。文章首先分析雷電過電壓的產(chǎn)生機理，采用ATP-EMTP電磁暫態(tài)仿真軟件搭建輸電線路繞擊和反擊模型，對繞擊和反擊進行仿真，基于理論分析和仿真結(jié)果，比較三種雷電過電壓之間的差異，基于時域分析和小波模極大值原理提取絕緣子電壓極性、桿塔入地電流極性與桿塔入地電流突變極性特征量，建立了基于極性鑒別的雷電過電壓識別方法。該方法同時引入絕緣子串電位差和桿塔入地電流兩組物理量，更為完整地描述雷擊物理過程，反映繞擊與反擊的本質(zhì)差異。與以往方法只引入線路電壓或線路電流單一物理量相比，方法的物理意義更為清晰直觀。同時，本文所提方法只提取信號的極性特征，不依賴雷電過電壓波頭的細節(jié)特征，不易受到?jīng)_擊電暈和行波傳輸過程中折反射的干擾，算法簡便直觀，，可靠性高。 基于對變電站常見過電壓的產(chǎn)生機理和波形特征的分析歸納，得到不同類型過電壓的暫態(tài)特征在時域的分布特點，提出各類型過電壓的暫態(tài)特征提取區(qū)間，使所提取的特征量具有更好的可分性，放大各類型過電壓間的差異。提出基于時域理論、頻域理論、小波理論和奇異值分解理論的特征提取方法，在過電壓相應(yīng)的特征提取區(qū)間提取特征量。本文對變電站內(nèi)常見混合過電壓進行了歸類，針對不同類型過電壓的產(chǎn)生機理和時序上的因果關(guān)系，基于小波模極大值的分布特點對時域相連的不同類型過電壓進行分解，實現(xiàn)混合過電壓的分解及特征提取。 本文對過電壓分類識別方法進行了討論，提出基于暫態(tài)特征時域分布特性的編碼分類方法，基于時域特征量對過電壓進行了初步識別�；谛〔〞r頻特征量和奇異值統(tǒng)計特征量，提出基于最小二乘支持向量機的過電壓識別方法。最后將本文所提分類識別方法有機整合，建立了變電站過電壓分層識別系統(tǒng)。經(jīng)實測數(shù)據(jù)驗證，本文提出的特征提取及分類識別方法能對電力系統(tǒng)過電壓進行有效辨識。
[Abstract]:With the expansion of power network scale and the continuous improvement of transmission capacity and voltage grade, the overvoltage of power system has caused more and more serious harm to the insulation of transmission lines and electrical equipment. Therefore, the study of power system overvoltage is an important issue to ensure the safe and reliable operation of power system. There are many kinds of overvoltages in power system. It is necessary to monitor all kinds of overvoltage signals in power system and identify fault types quickly and accurately to deal with faults and improve insulation coordination. In this paper, lightning overvoltage and substation overvoltage on transmission line are studied. In this paper, firstly, the mechanism of lightning overvoltage is analyzed, and the ATP-EMTP electromagnetic transient simulation software is used to build the transmission line wound failure and counterattack model, and the simulation results are based on the theoretical analysis and simulation results. By comparing the differences of three kinds of lightning overvoltages, the polarity of insulator voltage, the polarity of tower ground current and the abrupt polarity of tower ground current are extracted based on time domain analysis and wavelet modulus maximum principle. A method of lightning overvoltage recognition based on polarity discrimination is established. This method also introduces two sets of physical quantities: the potential difference of insulator string and the ground current of tower. The method describes the physical process of lightning stroke more completely and reflects the essential difference between round strike and counterattack. Compared with the single physical quantity of line voltage or line current, the physical meaning of the method is clearer and more intuitive. At the same time, the method proposed in this paper only extracts the polar characteristics of the signal, does not depend on the detailed characteristics of the lightning overvoltage wave head, and is not easy to be interfered by the shock corona and the refractive reflection during the traveling wave transmission. The algorithm is simple and intuitive and has high reliability. Based on the analysis of generation mechanism and waveform characteristics of common overvoltages in substations, the distribution characteristics of transient characteristics of different types of overvoltages in time domain are obtained, and the extraction interval of transient characteristics of different types of overvoltages is proposed. The extracted features have better separability and amplify the differences between different types of overvoltages. A feature extraction method based on time domain theory, frequency domain theory, wavelet theory and singular value decomposition theory is proposed. In this paper, the common mixed overvoltages in substations are classified. According to the generation mechanism of different types of overvoltages and the causality in time series, different types of overvoltages connected in time domain are decomposed based on the distribution characteristics of wavelet modulus maximums. The decomposition and feature extraction of hybrid overvoltage are realized. In this paper, the recognition method of overvoltage classification is discussed, and the coding classification method based on the time-domain distribution characteristics of transient features is proposed, and the primary recognition of overvoltage is carried out based on the time-domain characteristic quantity. Based on wavelet time-frequency characteristic and singular value statistical feature, an overvoltage recognition method based on least squares support vector machine (LS-SVM) is proposed. Finally, a hierarchical recognition system for substation overvoltage is established by integrating the classification and recognition methods proposed in this paper. The experimental results show that the proposed feature extraction and classification recognition method can effectively identify the overvoltage in power system.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM863

【參考文獻】

相關(guān)期刊論文 前10條

1 李天云,趙妍,季小慧,李楠;HHT方法在電力系統(tǒng)故障信號分析中的應(yīng)用[J];電工技術(shù)學(xué)報;2005年06期

2 楊麗君,廖瑞金,孫才新,梁帥偉,程渙超;基于Fisher判別法的油紙絕緣老化階段識別[J];電工技術(shù)學(xué)報;2005年08期

3 杜林;戴斌;陸國俊;孫才新;王有元;;基于S變換局部奇異值分解的過電壓特征提取[J];電工技術(shù)學(xué)報;2010年12期

4 王夢云;薛辰東;;1995～1999年全國變壓器類設(shè)備事故統(tǒng)計與分析[J];電力設(shè)備;2001年01期

5 何正友,錢清泉;電力系統(tǒng)暫態(tài)信號分析中小波基的選擇原則[J];電力系統(tǒng)自動化;2003年10期

6 李天云,趙妍,李楠;基于EMD的Hilbert變換應(yīng)用于暫態(tài)信號分析[J];電力系統(tǒng)自動化;2005年04期

7 周凱;張濤;董秀成;張彼德;王軍;席世友;;基于電容分壓的配電網(wǎng)過電壓在線監(jiān)測[J];電力系統(tǒng)自動化;2007年21期

8 張峰;梁軍;張利;

本文編號：2320665