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Bayesian Inference of Power System Insulation Reliability in the Presence of Voltage Harmonics

机译:电压谐波存在下电力系统绝缘可靠性的贝叶斯推断

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摘要

This article illustrates a Bayesian inference methodology for the parametric evaluation of the reliability of power system components in the presence of voltage harmonics. The methodology starts from an experimentally-based life model for solid insulation under distorted voltage, which belongs to the class of the popular Inverse Power Model. Thereafter, a novel approach is developed for building the prior distribution of the unknown life model parameters, described by a joint Normal distribution, that implies a Lognormal model for the hazard rate and the Mean Time To Failure. The applicability and efficiency of the proposed Bayesian methodology is checked by means of a broad amount of Monte Carlo simulations performed for the insulation of power capacitors and cables subjected to harmonic voltages. The results prove the satisfactory behavior of the Bayesian methodology especially for quite small samples; this is an important outcome, since - as well known in the case of real power systems -small samples are a common practical case.
机译:本文说明了用于在电压谐波存在下对电力系统组件的可靠性进行参数评估的贝叶斯推理方法。该方法从扭曲的电压下基于实验的固体绝缘寿命模型开始,该模型属于流行的逆功率模型。此后,开发了一种新颖的方法来建立未知生命模型参数的先验分布,用联合正态分布描述,这暗示了危险率和平均失效时间的对数正态模型。通过对受谐波电压影响的功率电容器和电缆进行绝缘的大量蒙特卡洛模拟,来检验所提出的贝叶斯方法的适用性和效率。结果证明了贝叶斯方法的令人满意的性能,特别是对于很小的样本而言。这是一个重要的结果,因为-在实际电力系统中众所周知-小样本是常见的实际情况。

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