【摘要】：電力變壓器是電力系統(tǒng)中重要的輸變電設(shè)備之一,在電力系統(tǒng)中處于樞紐地位,其運(yùn)行的安全可靠性直接關(guān)系到電力系統(tǒng)的安全。對(duì)變壓器進(jìn)行準(zhǔn)確的故障診斷,把握變壓器的狀態(tài),對(duì)于保證其安全穩(wěn)定運(yùn)行有著重要的意義。變壓器潛伏性故障發(fā)展時(shí)間較長(zhǎng),目前比較有效的檢測(cè)手段是油中溶解氣體分析技術(shù)(Dissolved Gas Analysis,DGA),可以發(fā)現(xiàn)變壓器是否發(fā)現(xiàn)故障,區(qū)分故障類別,并且對(duì)故障的嚴(yán)重程度進(jìn)行判斷。此外,對(duì)變壓器的潛伏性故障故障率做出準(zhǔn)確的估計(jì),對(duì)于指導(dǎo)變壓器的運(yùn)維等生產(chǎn)活動(dòng)也有著重要的意義。基于以上背景,本文主要圍繞變壓器故障診斷和潛伏性故障的故障率估計(jì)方法展開(kāi)研究。本文首先分析變壓器故障類型以及變壓器故障時(shí)油中溶解氣體的特征,并對(duì)目前應(yīng)用于電力設(shè)備故障診斷的人工智能方法及其優(yōu)缺點(diǎn)進(jìn)行綜述;根據(jù)極限學(xué)習(xí)機(jī)方法的特點(diǎn)及優(yōu)勢(shì),建立了基于極限學(xué)習(xí)機(jī)的故障分類模型,通過(guò)算例驗(yàn)證該模型在故障診斷方面的有效性,為基于DGA的變壓器故障診斷提供一種新思路。然后,本文在熱動(dòng)力學(xué)中焓的概念基礎(chǔ)上,通過(guò)對(duì)變壓器油分解化學(xué)反應(yīng)進(jìn)行分析,根據(jù)標(biāo)準(zhǔn)生成焓對(duì)不同故障氣體進(jìn)行加權(quán),引入能量加權(quán)DGA(Energy Weighted DGA,EWDGA)概念,分析其在變壓器故障嚴(yán)重程度判斷方面的應(yīng)用,并利用算例說(shuō)明EWDGA在判別故障程度時(shí)比傳統(tǒng)的產(chǎn)氣率數(shù)據(jù)有著更客觀的判斷。最后,本文基于EWDGA和馬爾可夫過(guò)程,提出計(jì)及能量加權(quán)產(chǎn)氣率數(shù)據(jù)的變壓器潛伏性故障的故障率估計(jì)方法,并通過(guò)算例說(shuō)明本文提出的方法與傳統(tǒng)方法相比,能夠更好的區(qū)分產(chǎn)氣率相同的狀態(tài)下,變壓器不同故障發(fā)展程度時(shí)的潛伏性故障的故障率。
[Abstract]:Power transformer is one of the important transmission and transformation equipment in power system. It is in the pivotal position in the power system. The safety and reliability of its operation is directly related to the security of power system. It is of great significance to make accurate fault diagnosis and grasp the state of transformer to ensure its safe and stable operation. The latent fault of transformer has a long development time. At present, the more effective detection method is dissolved gas analysis technology (Dissolved Gas Analysis,DGA) in oil. It can find out whether the transformer finds fault, distinguish the type of fault, and judge the severity of fault. In addition, it is of great significance to estimate the latent failure rate of transformers for guiding the operation and maintenance of transformers. Based on the above background, this paper focuses on transformer fault diagnosis and fault rate estimation of latent faults. This paper first analyzes the types of transformer faults and the characteristics of dissolved gases in oil when transformer faults occur, and summarizes the current artificial intelligence methods used in fault diagnosis of power equipment and their advantages and disadvantages. According to the characteristics and advantages of extreme learning machine, a fault classification model based on ultimate learning machine is established. The validity of the model in fault diagnosis is verified by an example, which provides a new way for transformer fault diagnosis based on DGA. Then, based on the concept of enthalpy in thermodynamics, by analyzing the decomposition chemical reaction of transformer oil, according to the standard enthalpy of formation, the concept of energy weighted DGA (Energy Weighted DGA,EWDGA is introduced. The application of EWDGA in judging the fault severity of transformer is analyzed, and an example is given to show that EWDGA has a more objective judgment than the traditional gas production rate data in judging the fault degree. Finally, based on EWDGA and Markov process, a fault rate estimation method for transformer latent faults considering energy-weighted gas production rate data is proposed, and an example is given to illustrate the comparison between the proposed method and the traditional method. It can better distinguish the failure rate of latent faults under the condition of the same gas production rate and different development degree of transformer faults.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TM407

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 唐鐵英;徐建文;;電容式電壓互感器潛伏性故障發(fā)現(xiàn)及原因分析[J];中國(guó)電力教育;2011年18期

2 陳超宗;時(shí)光;余維祥;李桂蘭;唐赤峰;;用液相色譜儀判斷充油電力設(shè)備潛伏性故障的初步探討[J];分析儀器;1982年02期

3 孫平;王志明;;淺議用氣相色譜法分析潛伏性故障[J];華北電力技術(shù);1992年02期

4 黎笑興;氣相色譜法在檢測(cè)變壓器潛伏性故障中的應(yīng)用[J];廣東電力;1996年02期

5 孫麗華;利用色譜分析判斷設(shè)備內(nèi)部潛伏性故障[J];黑龍江電力技術(shù);1998年05期

6 周志敏;色譜分析在變壓器潛伏性故障診斷中的應(yīng)用[J];大眾用電;2003年11期

7 趙銘剛;;色譜分析在充油電氣設(shè)備內(nèi)部潛伏性故障診斷中的應(yīng)用[J];中國(guó)新技術(shù)新產(chǎn)品;2010年02期

8 倪健;變壓器內(nèi)部潛伏性故障的診斷[J];農(nóng)村電氣化;2001年05期

9 劉艷蘋(píng);;氣相色譜應(yīng)用于充油電氣設(shè)備內(nèi)部潛伏性故障的診斷[J];內(nèi)蒙古石油化工;2011年12期

10 宋潔;杜正旺;;主變壓器潛伏性故障的檢測(cè)與分析[J];電氣制造;2013年08期

相關(guān)會(huì)議論文 前1條

1 張瑞春;姜吉平;;用氣相色譜法檢測(cè)變壓器潛伏性故障幾種判斷方法的分析[A];華東六省一市電機(jī)工程（電力）學(xué)會(huì)輸配電技術(shù)研討會(huì)2002年年會(huì)山東電機(jī)工程學(xué)會(huì)交流論文集[C];2002年

相關(guān)碩士學(xué)位論文 前1條

1 袁錦浩;基于能量加權(quán)DGA的變壓器潛伏性故障診斷及故障率估計(jì)方法[D];上海交通大學(xué);2015年

，

本文編號(hào)：2272582