School of Mathematical Sciences, University Sains Malaysia, Penang, Malaysia.
PLoS One. 2013 Aug 1;8(8):e69716. doi: 10.1371/journal.pone.0069716. Print 2013.
The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter [Formula: see text] and shape parameters [Formula: see text] and [Formula: see text]. Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models.
由于电力在日常生活和各个行业中的广泛应用，配电系统的可靠性是一个当代研究领域。然而，文献中仅有少量研究论文对此进行探讨。本文提出了一种基于平均故障间隔时间评估 33/11 千伏高功率站可靠性的方法。本文的目的是通过故障间隔时间找到故障数据的最佳拟合。我们确定了站中所有组件的参数估计。我们还估计了每个组件和整个系统的可靠性值。故障间隔时间的最佳拟合分布是一个三参数 Dagum 分布，具有尺度参数[公式：见文本]和形状参数[公式：见文本]和[公式：见文本]。我们的分析表明，每个 30 天可靠性值下降了 38.2%。我们相信，目前的论文是第一个解决这个问题及其分析的论文。因此，本研究中的结果反映了其创新性。我们还建议将这些结果用于电力系统，用于维护电力系统模型和预防性维护模型，以提高其实用性。
