本文選題：變壓器 + 絕緣狀態(tài)��； 參考：《昆明理工大學》2014年碩士論文

【摘要】：變壓器作為電網(wǎng)中能量轉(zhuǎn)換、傳輸?shù)暮诵?是電網(wǎng)安全的第一道防御系統(tǒng)中的關(guān)鍵樞紐設(shè)備。電力變壓器健康水平和運行狀態(tài)的判斷主要是依靠定期檢修的方式,但這種方式卻忽略了電力變壓器的實際狀態(tài),沒有根據(jù)檢測量信息本身所表現(xiàn)出來趨勢或者變化規(guī)律進行深入發(fā)掘,亦沒有從“信息驅(qū)動”的角度來考慮,忽略了變壓器潛在的狀態(tài)變化,也就很難實現(xiàn)變壓器的狀態(tài)估計。 絕緣是電氣設(shè)備結(jié)構(gòu)中的重要組成部分,隨著電力系統(tǒng)電壓等級的提高,絕緣已成為電氣設(shè)備中的薄弱環(huán)節(jié)。電力設(shè)備絕緣遭到損壞引起事故時,電力系統(tǒng)就不能安全穩(wěn)定地運行,也給國民經(jīng)濟造成巨大損失。變壓器中最廣泛使用的絕緣材料是油浸紙絕緣,油浸紙絕緣系統(tǒng)在運行中受到電、熱、機械等多種作用下會不斷老化。 針對電力變壓器面臨著日益嚴重的絕緣老化問題,發(fā)生事故的概率不斷增加,同時,由于電力變壓器的絕緣狀態(tài)評估受到多種內(nèi)部劣化和老化因素的約束,且影響程度又不盡相同。因此,通過深入研究基于物聯(lián)網(wǎng)的信息聚合架構(gòu)及各種信息聚合算法,根據(jù)變壓器的絕緣老化機理,采用相對劣化度來衡量變壓器絕緣狀態(tài)劣化程度,實現(xiàn)變壓器絕緣狀態(tài)的劃分。研究了核主成分分析和支持向量機的變壓器絕緣狀態(tài)評估模型,并提出基于典型相關(guān)分析的變壓器絕緣狀態(tài)評估信息聚合模型,根據(jù)相關(guān)性分析的結(jié)果對變壓器絕緣進行決策,確定變壓器絕緣運行狀態(tài),應用實例分析表明該模型的有效性和優(yōu)越性。 基于典型相關(guān)分析的變壓器絕緣信息聚合模型,融合了全局特征和局部特征,獲得了較佳的變壓器絕緣參量提取效果,達到了智能處理海量數(shù)據(jù)的功能,實現(xiàn)對變壓器進行有效的絕緣狀態(tài)評估,可以用來指導變壓器的運行維護和狀態(tài)檢修,延長變壓器的使用壽命,使變壓器更為經(jīng)濟、高效運行。
[Abstract]:Transformer, as the core of energy conversion and transmission in power grid, is the key hub equipment in the first defense system of power grid security. The health level and operation state of power transformers are judged mainly by the way of regular maintenance, but this way ignores the actual state of power transformers. It is difficult to realize the state estimation of the transformer if the trend or the change law of the measurement information itself is not deeply explored, nor is it considered from the angle of "information drive", and the potential state change of the transformer is ignored, so it is very difficult to realize the state estimation of the transformer. Insulation is an important part of electrical equipment structure. With the improvement of power system voltage grade, insulation has become a weak link in electrical equipment. When the insulation of power equipment is damaged, the power system can not operate safely and stably, and it also causes huge losses to the national economy. The most widely used insulating material in transformers is oil-impregnated paper insulation. The oil-impregnated paper insulation system will aging continuously under the action of electricity, heat, machinery and so on. In view of the increasingly serious insulation aging problem faced by power transformers, the probability of accidents is increasing. At the same time, due to the variety of internal deterioration and aging factors, the insulation state evaluation of power transformers is restricted. And the degree of influence is different. Therefore, through the in-depth study of information aggregation architecture based on the Internet of things and various information aggregation algorithms, according to the insulation aging mechanism of transformers, the relative deterioration degree is adopted to measure the degree of insulation deterioration of transformers. The insulation state of transformer is divided. Based on kernel principal component analysis (KPCA) and support vector machine (SVM), an evaluation model of transformer insulation state is proposed, and an information aggregation model based on canonical correlation analysis is proposed to make decisions on transformer insulation according to the results of correlation analysis. The operation state of transformer insulation is determined, and the application examples show that the model is effective and superior. The transformer insulation information aggregation model based on canonical correlation analysis combines the global and local features, obtains a better effect of transformer insulation parameter extraction, and achieves the function of intelligent processing of mass data. It can be used to guide the operation maintenance and condition maintenance of transformers, prolong the service life of transformers, and make the transformers more economical and efficient.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM41

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