Reliability performance of distribution network by various probability distribution functions
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 distributi...
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Institute of Advanced Engineering and Science
2023
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Online Access: | http://umpir.ump.edu.my/id/eprint/37595/1/Reliability%20performance%20of%20distribution%20network%20by%20various%20probability%20distribution%20functions.pdf http://umpir.ump.edu.my/id/eprint/37595/ https://doi.org/10.11591/ijece.v13i2.pp2316-2325 https://doi.org/10.11591/ijece.v13i2.pp2316-2325 |
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my.ump.umpir.375952023-08-29T07:28:12Z http://umpir.ump.edu.my/id/eprint/37595/ Reliability performance of distribution network by various probability distribution functions Noorfatin Farhanie, Mohd Fauzi Nur Nabihah Rusyda, Roslan Mohd Ikhwan, Muhammad Ridzuan T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering 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. Institute of Advanced Engineering and Science 2023-04 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/37595/1/Reliability%20performance%20of%20distribution%20network%20by%20various%20probability%20distribution%20functions.pdf Noorfatin Farhanie, Mohd Fauzi and Nur Nabihah Rusyda, Roslan and Mohd Ikhwan, Muhammad Ridzuan (2023) Reliability performance of distribution network by various probability distribution functions. International Journal of Electrical and Computer Engineering, 13 (2). pp. 2316-2325. ISSN 2088-8708. (Published) https://doi.org/10.11591/ijece.v13i2.pp2316-2325 https://doi.org/10.11591/ijece.v13i2.pp2316-2325 |
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T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Noorfatin Farhanie, Mohd Fauzi Nur Nabihah Rusyda, Roslan Mohd Ikhwan, Muhammad Ridzuan Reliability performance of distribution network by various probability distribution functions |
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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. |
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Article |
author |
Noorfatin Farhanie, Mohd Fauzi Nur Nabihah Rusyda, Roslan Mohd Ikhwan, Muhammad Ridzuan |
author_facet |
Noorfatin Farhanie, Mohd Fauzi Nur Nabihah Rusyda, Roslan Mohd Ikhwan, Muhammad Ridzuan |
author_sort |
Noorfatin Farhanie, Mohd Fauzi |
title |
Reliability performance of distribution network by various probability distribution functions |
title_short |
Reliability performance of distribution network by various probability distribution functions |
title_full |
Reliability performance of distribution network by various probability distribution functions |
title_fullStr |
Reliability performance of distribution network by various probability distribution functions |
title_full_unstemmed |
Reliability performance of distribution network by various probability distribution functions |
title_sort |
reliability performance of distribution network by various probability distribution functions |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2023 |
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http://umpir.ump.edu.my/id/eprint/37595/1/Reliability%20performance%20of%20distribution%20network%20by%20various%20probability%20distribution%20functions.pdf http://umpir.ump.edu.my/id/eprint/37595/ https://doi.org/10.11591/ijece.v13i2.pp2316-2325 https://doi.org/10.11591/ijece.v13i2.pp2316-2325 |
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