電力變壓器不同繞組導(dǎo)線換位方式下環(huán)流損耗對(duì)比分析
任亞軍,韓軍鋒,張峰
(國(guó)網(wǎng)洛陽(yáng)供電公司,河南 洛陽(yáng) 471000)
摘 要:變壓器隨著容量的不斷增大,線圈的漏磁場(chǎng)不斷增強(qiáng),從而在運(yùn)行時(shí),導(dǎo)致各導(dǎo)線間感應(yīng)出無(wú)用的環(huán)流損耗迅速增加,為了減小環(huán)流損耗,需要進(jìn)行導(dǎo)線換位。研究了有限元分析方法對(duì)單相電力變壓器模型的仿真,提出了普通克里金模型與粒子群算法相結(jié)合的新型高效全局優(yōu)化算法,并比較分析了不同繞組導(dǎo)線換位方式下的變壓器環(huán)流損耗大小,得到了最小環(huán)流損耗的最佳匝數(shù)分配方案。該方法不但保證了優(yōu)化的準(zhǔn)確度,而且進(jìn)一步縮短了優(yōu)化中的計(jì)算時(shí)間。優(yōu)化結(jié)果與當(dāng)前應(yīng)用于工業(yè)的設(shè)計(jì)方案相比,其環(huán)流損耗得到了很大的降低。
關(guān)鍵詞:電力變壓器;繞組導(dǎo)線換位;環(huán)流損耗;克里金模型;粒子群算法
中圖分類(lèi)號(hào):TM41 文獻(xiàn)標(biāo)識(shí)碼:A 文章編號(hào):1007-3175(2021)01-0030-05
Comparative Analysis of Circulating Current Loss in Power
Transformer with Different Winding Wire Transpositions
REN Ya-jun, HAN Jun-feng, ZHANG Feng
(State Grid Luoyang Power Supply Company, Luoyang 471000, China)
Abstract: As the capacity of the transformer continues to increase, the leakage magnetic field of the coil continues to increase, which leads to a rapid increase in the useless circulating current loss induced between the wires during operation. In order to reduce the circulatingcurrent loss, the wire needs to be transposed. The simulation of the single-phase power transformer model by the finite element analysismethod is studied, and a new efficient global optimization algorithm combining the ordinary Kriging model and the particle swarm algorithmis proposed. It also compares and analyzes the circulating current loss of the transformer under different winding wire transposition methods,and obtains the optimal number of turns distribution scheme with the smallest circulating current loss. This method not only guarantees theaccuracy of optimization, but also further shortens the calculation time in optimization. Compared with the design scheme currently appliedin industry, the optimized result has greatly reduced the circulating current loss.
Key words: power transformer; winding wire transposition; circulating current loss; Kriging model; particle swarm optimization
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