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Modelling of Failures of Electric Network Elements Based on Regression Models Accounting the Trend

机译:基于回归模型的电网元件故障建模趋势

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The article analysed various approaches to modelling emergency outages on electrical networks, some of which were previously used by the authors to predict and probabilistic assessment of the studied parameter. Based on the correlation analysis, it was revealed that the number of emergency shutdowns that took place in the city of Irkutsk in 2010–2017 is significantly affected by the heat parameter, which is taken as the sum of the average monthly temperatures. Since it was previously revealed that in the series of emergency outages for some years and months there are significant linear and polynomial trends, time is taken as the second factor. According to the results obtained, linear and nonlinear factor models calculated from data for a given year are equally significant. Monthly series of outages in most cases more accurately describes models with a polynomial trend. The obtained regression equations can be used to model emergency outages with a given probability and to assess the risks of their occurrence.
机译:本文分析了各种方法来建立电网的紧急情况,其中一些是由作者使用的,以预测研究的参数的概率评估。基于相关性分析,据透露,2010 - 2017年在伊尔库茨克市发生的紧急停机数受到热参数的显着影响,这是作为平均每月温度的总和。由于以前透露,在一系列紧急情况下有多年和几个月存在显着的线性和多项式趋势,因此时间被视为第二因素。根据所获得的结果,由给定年份的数据计算的线性和非线性因子模型同样显着。在大多数情况下每月的中断更准确地描述具有多项式趋势的模型。所获得的回归方程可用于使用给定概率模拟紧急情况并评估其发生的风险。

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