Development of Maintenance Management System to Improve Reliability of Power Supply in Medium Voltage Distribution Network: A Case of TANESCO, Kinondoni North Region

Said Abdallah Salanga; Sosthenes Karugaba; Respicius Kiiza

doi:10.37284/ijar.8.1.2713

Said Abdallah Salanga Dar es Salaam Institute of Technology
Sosthenes Karugaba Dar es Salaam Institute of Technology
Respicius Kiiza Dar es Salaam Institute of Technology

DOI: https://doi.org/10.37284/ijar.8.1.2713

Keywords: Reliability of Power Supply, Medium Voltage Distribution Network, Distribution Automation, Maintenance and Operation Management, Reliability Indices, Development of Maintenance Management System

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Abstract

The reliability of the power supply in medium voltage distribution networks is crucial in the Kinondoni North region due to the growing demand for reliable electricity, increasing by approximately 20 MW per year. However, power supply reliability is compromised by several factors such as aging infrastructure, equipment failures, vandalism, natural disasters like storms and floods etc. These issues contribute to faults in the distribution feeders, causing power interruptions. Key challenges include identifying the location of faults, restoring power efficiently, and managing network maintenance. This research aims to develop a Maintenance Management System (MMS) to manage both maintenance and operational activities in medium voltage distribution networks, enhancing the efficiency of operations and improving power supply reliability in medium voltage distribution networks in the region. To achieve this, factors affecting maintenance management were identified through a literature review, assessment, and site surveys. Data were collected and analyzed using SPSS and a regression model was developed to improve reliability. The analysis revealed six most significant factors out of ten factors that influence power supply reliability are Budget Constraints, Network Design, Fault Detection & Isolation Equipment, Maintenance Practices, Data and Information Management, and Skilled Labor. The model developed had high predictive accuracy, with R=0.915, indicating that these factors significantly predict the reliability of the power supply. To improve reliability, the study recommends adopting the reliability performance model and MMS in the Kinondoni north region. Key recommendations include investing in workforce development, training employees on advanced fault detection technologies, implementing smart grid technologies for real-time data monitoring, optimizing grid design with redundancy, and adopting predictive maintenance based on condition monitoring. These strategies will reduce downtime and improve the overall reliability of the power supply in the medium voltage distribution network

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