Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network

N. Dahlan, N. Kasuan, A. S. Ahmad
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引用次数: 2

Abstract

Electrical power system lines sometimes pass along the coastal regions and transverse through the industrial areas of the Peninsular Malaysia. The phenomenon of salt blown from the sea to the land at the coastal area was causing salt deposition to the transformer bushing which contaminating the bushing surfaces and produced leakage current. Hence, it triggering to insulator flashover and finally the hot power arc will damage the bushing. This paper estimates leakage current level by modeling it as a function of various meteorological parameters using Hybrid Multilayered Perceptron Networks (HMLP) with Modified Recursive Prediction Error (MRPE) learning algorithms. The results are also compared with the regression analysis done previously. Meteorological parameters and leakage current data are based on the real measured data collected at YTL Paka Power Station in Terengganu.
用HMLP神经网络模拟悬挂式高压绝缘子泄漏电流的各种气象影响
电力系统线路有时沿着沿海地区,横向穿过马来西亚半岛的工业区。在沿海地区,海水吹盐到陆地的现象使盐沉积在变压器套管上,污染了套管表面,产生泄漏电流。因此,它触发绝缘子闪络,最终产生热电弧损坏套管。本文利用混合多层感知器网络(HMLP)和改进的递归预测误差(MRPE)学习算法,将泄漏电流水平建模为各种气象参数的函数,从而估计泄漏电流水平。并与之前的回归分析结果进行了比较。气象参数和泄漏电流数据基于在登嘉楼YTL Paka电站收集的实际测量数据。
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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