Reliability Enhancement of Distribution System by Using Feeder Reconfiguration (Case Study: Mekelle City Distribution System)

Abstract

Equipment failures and customer interruptions are the primary factors that affect distribution reliability. In many developing nations, including Ethiopia, reliability modeling and evaluation of distribution networks receive less attention "compared to" generating and transmitting systems. Since electric power is now used directly or indirectly for many of our activities, the utility should provide dependable electricity every day of the year to meet consumer demands and enable employees to do their jobs as efficiently as possible. However, several fault types affect the power supply’s reliability and quality. Power quality issues and interruptions are common in Mekelle distribution substation. Short-circuit faults, whether permanent or transient, system overloading and other factors are the primary causes of these interruptions. As a result, consumers are not receiving reliable power. The main goal of this work is the enhancement of the 15 kV side Mekelle distribution networks at a reasonable cost. Because several factors are causing power outages that mostly affect the 15 kV side. The reliability assessment has been done on fifteen feeders of the 15 kV Mekelle city distribution network. A reliability assessment of feeders on the 15 kV side has been carried out in order to assess the effectiveness of the current system and predict upcoming reliability evaluations. All the interruption data of five years (2011 E.C. up to 2015 E.C.) has been used which have been collected from Mekelle substation as well as north region Ethiopian electric power. Different alternatives have been assessed using ETAP 19.0.1 software method and the alternative with low SAIDI, SAIFI and EENS with a reasonable cost has been preferred. The reliability of Mekelle city distribution network has been enhanced significantly by implementing auto-reclosers that are justified economically. Even if the ambiguity of the input data is taken into account, SAIFI has been reduced by 59% as compared with the average reliability indices values of the existing system. In the similar way SAIDI and EENS have been decreased by 61% and 78.1% respectively.