基于神经网络的三级温度特性曲线的电力电缆老化故障率估计
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国网宁夏电力有限公司电力科学研究院

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宁夏重点研发计划项目(2020YCYF0112)


The aging failure rate estimation of power cable under three-stage temperature characteristic curve based on neural network
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Ningxia Electrical Power Research Institute of State Grid,Yinchuan,750011

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    摘要:

    电流产生的热效应是影响电缆使用寿命和老化故障的主要原因。因此,建立电缆温度特性模型极其重要,电力企业应能够正确估计配电网电缆的相关老化故障率。目前,现有的电缆故障率的估计是在额定温度下进行计算,并没有考虑实际运行中温度变化的影响。因此,本文采用一种基于人工神经网络的方法来估计电缆的最高温度,该温度变化满足一定的日负荷曲线。人工神经网络只需要四个容易获取的输入变量,利用电缆绝缘组合电热寿命模型,对预测温度曲线各阶段的寿命损失进行了估计。最后,利用该寿命模型和概率失效模型预测未来一段时间内电力电缆的故障率。结果表明,失效概率的估计与实际结果一致性好,说明所估算的电缆温度三级逐步变化曲线能够真实反映电缆瞬态温度变化。

    Abstract:

    The thermal effect of current is the main cause of cable service life and aging failure. Therefore, it is very important to establish the cable temperature characteristic model, power enterprises should be able to correctly estimate the related aging failure rate of distribution network cables. At present, the existing cable failure rate estimates are calculated at the rated temperature and do not take into account the effect of actual operating temperature changes. Therefore, a method based on artificial neural network is used to estimate the maximum temperature of the cable. The artificial neural network only needs four easily obtained input variables, and the life loss at each stage of the predicted temperature curve is estimated by using the combined electric heating life model of cable insulation. Finally, the life model and probability failure model are used to predict the failure rate of power cables in the future. The results show that the estimation of failure probability is in good agreement with the actual results, which indicates that the three-stage gradual change curve of cable temperature can truly reflect the cable transient temperature change.

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  • 收稿日期:2020-10-22
  • 最后修改日期:2020-11-19
  • 录用日期:2020-12-07
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