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首页> 外文期刊>International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications >Lightning performance identification of high voltage transmission lines using artificial neural networks
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Lightning performance identification of high voltage transmission lines using artificial neural networks

机译:高压输电线路雷电性能的人工神经网络识别

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The paper presents a novel approach to lightning performance identification of high voltage transmission lines using artificial neural networks (ANNs). This approach is described in detail and results obtained by its application on an operating 400 kV Hellenic transmission line are presented. The conventional multilayer perceptron (MLP) technique, based on a backpropagation algorithm was considered in order to train the model. Actual input and output data collected from operating Hellenic high voltage transmission lines were used in the training process. The computed lightning failure rate is compared with real records of outage rate and with results obtained using the analytical algorithms. The presented methodology can be proved valuable to the studies of electric power systems designers, intended in a more effective protection of transmission lines against lightning strokes.
机译:本文提出了一种使用人工神经网络(ANN)识别高压输电线路雷电性能的新方法。对该方法进行了详细说明,并介绍了其在运行中的400 kV希腊输电线路上的应用所获得的结果。为了训练模型,考虑了基于反向传播算法的常规多层感知器(MLP)技术。在训练过程中使用了从运行中的希腊高压输电线路收集的实际输入和输出数据。将计算出的雷击失败率与实际中断率记录进行比较,并与使用解析算法获得的结果进行比较。可以证明所提出的方法对于电力系统设计者的研究是有价值的,其目的在于更有效地保护输电线路免受雷击。

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