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Reliability performance of distribution network by various probability distribution functions

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 2 (2023)

DOI
10.11591/ijece.v13i2.pp2316-2325
ISSN
2722-2578, 2088-8708
Published
2023-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Electricity is one of the essential sources for the daily basis activities. The continuous electricity supplied to the customers is one of the main goals for electricity provider. Reliability is one of the main aspects that is focused more on the planning of the power system especially in distribution network. The performance of reliability in the system is evaluated with three main reliability indices: system average interruption frequency index, system average interruption duration index, and customer average interruption duration index. These indices will only give information about the overall condition of the power system without showing the details about the specific of the consumers such as the amount interruptions experienced by customer in the system. In this paper, probability distribution function (PDF) observing the behavior of the components in the system is used in the reliability analysis. Weibull distribution, also known as Weibull family, is one of the most common PDF used in reliability analysis. As Weibull distribution is also related to several distributions, such as exponential and Rayleigh, these types of distributions are applied in the output reliability analysis to observe the performance of reliability in the system. IEEE 9-bus is used as distribution network and carried out using Monte-Carlo simulation.

Collaboration network of the authors

3 authors · 3 co-authorship links

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  • Universiti Malaysia Pahang Al-Sultan Abdullah
  • Different organisations
  • Same organisation
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Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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