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Study of Distribution Transmission Line Lightning Stroke Risk Forecasting Based on Nonlinear Time Series Analysis

机译:基于非线性时间序列分析的配电线路雷击风险预测研究

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To solve the problem of the risk forecasting of distribution system directly stroke, a lighting stroke risk forecasting model of distribution transmission line based on nonlinear time series analysis is proposed in the paper. The duration of the thunder and lightning is the key of lighting stroke risk predicting, and other circumstance conditions such as temperature, humidity, atmospheric pressure, are also great influence on it. The observed values of these five circumstance conditions can be treated as a nonlinear time series model. An artificial neural networks model is proposed in the paper to solve the nonlinear time series model of stroke risk forecasting. The ANNs model is consisted of five artificial neural networks which is used to prediction the circumstance conditions time series, and then employed to prediction the lighting stroke risk of the transmission line. A series of simulation show that the results of the predicting model is acceptable in engineering application.
机译:为解决配电系统直接行程的风险预测问题,提出了一种基于非线性时间序列分析的配电线路照明行程风险预测模型。雷电的持续时间是预测雷击风险的关键,温度,湿度,大气压等其他情况也对其影响很大。这五个情况条件下的观测值可以视为非线性时间序列模型。本文提出了一种人工神经网络模型来解决中风风险预测的非线性时间序列模型。人工神经网络模型由五个人工神经网络组成,用于预测环境条件时间序列,然后用于预测输电线路的雷击风险。一系列仿真表明,预测模型的结果在工程应用中是可以接受的。

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