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Quantification of aleatory and epistemic uncertainty in bulk power system reliability evaluation

机译:大型电力系统可靠性评估中偶然和认识不确定性的量化

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Uncertainty can be generally classified as aleatory uncertainty, related to random behaviour, and epistemic uncertainty, related to a lack of information. This paper studies the uncertainty in bulk power system reliability assessment. It analyses the source of uncertainty in components outage model and refers it to the congruous uncertianty forms. This leads to the characterization of outage model uncertainty by a mixed aleatory-epistemic model. In consequence, the paper suggests two methods for representing and quantifying the effect of mixed aleatory-epistemic uncertainty on system reliability indices. These methods are second order probability and evidence theory. The paper validates the feasibility of the two methods by conducting case studies on the IEEE-RTS system using the non-sequential Monte Carlo simulation approach. The mixed aleatory-epistemic model is shown to provide more detailed estimate of uncertainty than the typical aleatory model.
机译:不确定性通常可分为与随机行为有关的偶然不确定性和与缺乏信息有关的认知不确定性。本文研究了大功率系统可靠性评估中的不确定性。它分析了组件故障模型中不确定性的根源,并将其称为完整的不合格形式。这导致通过混合偶然性-流行病模型来表征中断模型的不确定性。因此,本文提出了两种方法来表示和量化混合的不确定性对系统可靠性指标的影响。这些方法是二阶概率论和证据论。本文通过使用非顺序蒙特卡罗模拟方法对IEEE-RTS系统进行案例研究,验证了这两种方法的可行性。混合的偶然性-流行病模型显示出比典型的偶然性模型更详细地估计不确定性。

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