油浸倒立式電流互感器主絕緣電場分析與優(yōu)化設(shè)計(jì)
本文選題:油浸倒立式電流互感器 切入點(diǎn):主絕緣 出處:《沈陽工業(yè)大學(xué)》2012年碩士論文 論文類型:學(xué)位論文
【摘要】:油浸倒立式電流互感器區(qū)別于傳統(tǒng)的正立式結(jié)構(gòu),將二次繞組與一次繞組集中置于整個產(chǎn)品的上部,避免了正立式電流互感器主絕緣位于產(chǎn)品底部易受潮的問題,減少了主絕緣因受潮而被擊穿的可能性,但同時也給產(chǎn)品的絕緣設(shè)計(jì)和工藝制造增添了一定的難度。 油浸式電流互感器在110kV電壓等級以上通常采用電容型油紙絕緣結(jié)構(gòu),即在主絕緣中嵌入電容屏來改善電場分布。針對于倒立式的特殊結(jié)構(gòu),增加電容屏的方式一般分為兩種:一種為端屏式結(jié)構(gòu),另一種則為主屏式結(jié)構(gòu)。本文采用主屏式結(jié)構(gòu),以220kV油浸倒立式電流互感器為研究對象,分析了主絕緣的物理結(jié)構(gòu)特點(diǎn),采用數(shù)值和解析兩種方法求解屏間電容,并驗(yàn)證了兩種方法的準(zhǔn)確性。根據(jù)倒立式電流互感器主屏式結(jié)構(gòu)的特點(diǎn),采用分層分段的方式建立電場分析的有限元模型,將二次側(cè)繞組與下引線部位分開,對于二次側(cè)繞組部位進(jìn)行三維有限元分析,對于下引線部位進(jìn)行二維有限元分析,并采用解析法驗(yàn)證了有限元計(jì)算電場的準(zhǔn)確性。根據(jù)電場分布以及最大場強(qiáng)位置,分析影響絕緣性能的主要因素,提出了優(yōu)化方案。 本文采用RBF神經(jīng)網(wǎng)絡(luò)動態(tài)響應(yīng)模型與遺傳算法相結(jié)合的方法對主屏結(jié)構(gòu)的油浸倒立式電流互感器的主絕緣結(jié)構(gòu)進(jìn)行優(yōu)化。根據(jù)動態(tài)神經(jīng)網(wǎng)絡(luò)的思想,建立動態(tài)響應(yīng)模型,使響應(yīng)模型跟隨最優(yōu)點(diǎn)的位置不斷更新、細(xì)化,避免了傳統(tǒng)響應(yīng)模型采樣點(diǎn)過多的缺陷;采用冪律標(biāo)定方法增強(qiáng)了遺傳算法的選擇功能。通過優(yōu)化降低了最大場強(qiáng),同時也使主絕緣整體的電場分布得到了改善。
[Abstract]:The oil-immersed inverted current transformer is different from the traditional vertical structure by concentrating the secondary winding and the primary winding on the upper part of the whole product, thus avoiding the problem that the main insulation of the vertical current transformer is located at the bottom of the product. It reduces the possibility of the main insulation being broken down by moisture, but it also adds some difficulties to the insulation design and process manufacture of the product. The oil-immersed current transformer usually adopts capacitive oil-paper insulation structure above 110 kV voltage level, that is, to improve electric field distribution by embedding capacitance screen in the main insulation. There are two ways to increase the capacitance screen: one is the end screen structure, the other is the main screen structure. In this paper, the main screen structure is adopted and the 220 kV oil-immersed inverted current transformer is taken as the research object, and the physical structure characteristics of the main insulation are analyzed. Numerical and analytical methods are used to solve the capacitance between screens, and the veracity of the two methods is verified. According to the characteristics of the main screen structure of the inverted current transformer, the finite element model of electric field analysis is established in a layered and piecewise manner. The secondary side winding is separated from the lower lead part, the secondary side winding part is analyzed by three-dimensional finite element method, and the lower lead part is analyzed by two-dimensional finite element method. The accuracy of finite element calculation of electric field is verified by analytical method. According to the distribution of electric field and the position of maximum field strength, the main factors affecting insulation performance are analyzed, and the optimization scheme is put forward. In this paper, RBF neural network dynamic response model combined with genetic algorithm is used to optimize the main insulation structure of oil-immersed inverted current transformer with main screen structure. According to the idea of dynamic neural network, the dynamic response model is established. The response model is updated and refined according to the optimal position, which avoids the defect that the traditional response model has too many sampling points. The power law calibration method is used to enhance the selection function of genetic algorithm, and the maximum field strength is reduced by optimization. At the same time, the electric field distribution of the main insulation is improved.
【學(xué)位授予單位】:沈陽工業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2012
【分類號】:TM452.3
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