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Parameter identification of power transformers thermal model via genetic algorithms

机译:基于遗传算法的电力变压器热模型参数辨识

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摘要

Recent studies by various authors have shown as the IEEE Transformer Loading Guide model and the more recent modified equations, proposed by the Working Group K3 of the IEEE 'Power System Relaying Committee', are lacking in accuracy in predicting the winding hottest-spot temperature of a power transformer in presence of overload conditions. this is mainly due to the deviation of the parameters of the thermal model of the power transformer in the presence of overload conditions. In the paper, a novel technique to identify the thermal parameters to be sued for the estimation of the hot-spot temperature is presented.
机译:各种作者的最新研究已将其作为《 IEEE变压器负载指南》模型,由IEEE“电力系统中继委员会”的工作组K3提出的最新修正方程式在预测绕组绕组最热点温度方面缺乏准确性。在过载情况下的电力变压器。这主要是由于在过载条件下电力变压器热模型参数的偏差。在本文中,提出了一种新颖的技术来识别要用于估算热点温度的热参数。

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