一种评估超高压变电站结冰严重程度的简单方法

C. Volat, F. Meghnefi, M. Farzaneh
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引用次数: 0

摘要

本文提出了一种评估特高压变电站结冰严重程度的简便方法。提出了一种基于超高压标准站绝缘子漏电流和外加电压监测的方法。通过对几次试验的LC演化进行简单的研究,确定了LC包络的演化分为两个不同的阶段,这两个阶段之间的过渡是明确的,并且与冰柱对棚间距的桥接有关。还观察到,第一阶段的持续时间仅取决于结冰速率,而不受施加的水电导率的影响。根据这些观测结果,可以使用人工神经网络(ANN)等特定工具来估计积雪区的结冰率。利用人工神经网络检测积冰的开始时间,计算第1周期的持续时间,并估计结冰率,这是积冰严重程度的最重要特征之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A simple method to assess ice built-up severity in EHV substations
This paper presents a simple method to assess the severity of ice built-ups in EHV substations. The proposed method is based on the monitoring of the leakage current (LC) and the applied voltage of an EHV standard station insulator. By simply studying the LC evolution of several experimental tests, it was established that the evolution of a LC envelope is divided in two distinct periods where the transition between these two periods is clearly identified and is correlated with the bridging of the shed spacing by icicles. It was also observed that the duration of the first period is only dependent of the icing rate and is not influenced by the applied water conductivity. From these observations, it is possible to estimate the icing rate of an accumulation using specific tools like artificial neural networks (ANN). ANN is used to detect the onset of the ice accumulation with permits to calculate the duration of Period 1 and estimate the icing rate which is one of the most important characteristic of ice built-up severity.
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