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Application of regression models to predict harmonic voltage and current growth trend from measurement data at secondary substations

机译:回归模型从二次变电站的测量数据预测谐波电压和电流增长趋势的应用

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This paper presents the applications of regression models to predict the future growth trend of total harmonic distortions (THD) of 40 power transformers from field measurement data. The prediction values are important and can be used for transformer planning. Those transformers which feed different types of customers reveal different harmonic characteristics. While the linear regression model is suitable for harmonic voltage distortion, the nonlinear exponential regression model is better for current. All transformers' harmonic voltage distortions follow with harmonic current distortions, that is, feeder loads are harmonic sources. The prediction harmonic values of regression analysis are lower than that from the method of average spread rate.
机译:本文介绍了回归模型的应用,可以根据现场测量数据预测40个电力变压器的总谐波失真(THD)的未来增长趋势。预测值很重要,可用于变压器规划。那些为不同类型的客户供电的变压器具有不同的谐波特性。线性回归模型适用于谐波电压失真,而非线性指数回归模型适用于电流。所有变压器的谐波电压失真都伴随着谐波电流失真,也就是说,馈线负载是谐波源。回归分析的预测谐波值低于平均扩散率方法的预测谐波值。

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