An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

This paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network.

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Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2025-09-01
DOI
https://doi.org/10.11591/ijpeds.v16.i3.pp1852-1864
Primary Topic
Power System Reliability and Maintenance
Type
article
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article

An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

Ngang Bassey Ngang, Evans Chinemezu Ashigwuike, Jacob Kehinde Ogunjuyigbe, Timothy Oluwaseun Araoye et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Power System Reliability and Maintenance
article

An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

Ngang Bassey Ngang, Evans Chinemezu Ashigwuike, Jacob Kehinde Ogunjuyigbe, Timothy Oluwaseun Araoye, Benson Stephen Adole, Kafayat Adeyemi, Isaac Ojochogwu Onuh, Solomon Bala Okoh, Iboi Endurance
article en

Abstract

This paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 16(3)
University of Nigeria (NG), University of Abuja (NG)
Openalex Percentile: Top 72%
Power System Reliability and Maintenance
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