用神经网络估计500kv超高压双回输电线路雷电过电压分析中停电率影响的概率参数

C. Jaipradidtham
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引用次数: 3

摘要

本文提出了用神经网络估计500kv超高压双回线路DL3deg和DT20deg雷电过电压分析中停电率影响的概率参数。本研究从确定临界闪络电压参数开始,给出了给定雷电浪涌性能水平所需的临界闪络电压。如果浪涌电压沿线路变化,则会影响系统的绝缘不受故障影响。这条故障线路在架空地线上会有若干次行程。线路中闪络效应产生的最大电压。浪涌电压发生的高斯频率、极值分布、临界行程电流。人工神经网络可以缩短塔闪络的发生概率和断网率。用程序对这些参数进行了估计,有效地提高了500kv双回输电线路设计的可靠性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probability parameter estimation of outage rate effects for lightning overvoltage analysis on 500 kV EHV double circuit transmission lines using neural networks
This paper presents the probability parameter estimating due to outage rate effects for lightning overvoltage analysis on 500 kV EHV double circuit transmission lines of type DL3deg and DT20deg by using neural networks. This research begins for parameter determining the critical flashover voltage: (CFO) required for a given lightning surge performance level is given. If the surge voltage varies along the line, the insulation of system from fault effect. This fault line will have a number of stroke on overhead ground wire. The maximum voltage from flashover effects in the lines. The Gaussian frequency of occurrence of surge voltage, the extreme value distribution, the critical stroke current. An artificial neural network can shorten the probability of flashover at tower and the outage rate. Estimation of the parameter using program give the results which are reliability of 500 kV double circuit transmission lines designs efficiently
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