The effect of quantization and sampling time on transformers thermal performance and parameters calculation

D. Tylavsky, Q. He, J. Si, G. McCulla, J. Hunt
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引用次数: 2

Abstract

Improving the utilization of transformers requires that the hot-spot and top-oil temperatures (HSTs and TOTs) be predicted accurately. Our experimentation with various discretization schemes and models, proved that many of the linear and nonlinear semi-physical and nonphysical models we were using to predict transformer TOT were correctly modeling the TOT behavior. Our experience convinced us that noisy input data and the absence of data on significant driving variables, not model deficiencies, were frustrating our attempts to reduce the prediction error further. In this paper, we discuss the body of research that leads us to these conclusions.
量化和采样时间对变压器热性能和参数计算的影响
提高变压器的利用率需要准确预测热点温度和顶油温度(HSTs和tot)。我们对各种离散化方案和模型的实验证明,我们用于预测变压器TOT的许多线性和非线性半物理和非物理模型都正确地模拟了TOT行为。我们的经验使我们确信,噪声输入数据和重要驱动变量数据的缺乏,而不是模型缺陷,使我们进一步减少预测误差的尝试受挫。在本文中,我们讨论了导致我们得出这些结论的研究主体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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