In Bahirdar city, frequent and protracted power outages have become a major issue. The life and economic activity of society have been significantly impacted by this issue. Power outages have a huge financial impact on both the industry and the power company. In comparison to the reliability standards set by Ethiopia and other European nations, the Bahir -dar City distribution system is unreliable. In this thesis in order to know the existing performance of Bahirdar radial distribution system historical reliability analysis is carried out using the collected data from Amhara region Ethiopian Electric Utility Bahirdar Bahirdar district SCADA centre and Bahirdar substation for the years 2020/2021 and 2021/2022 G.C. The system reliability indices (SAIFI=276.37 int./yr, SAIDI=1127.71 hr/yr , ASAI=87 %, EENS=5018.31 MWhr/yr and TCENS=8,430760.8 Birr/yr.) of the study area show that Bahirdar city distribution system is unreliable as compared to standard practices by other European countries and Ethiopia’s reliability requirement. The selected 15kV outgoing feeder from switching station R1-G3 supplies electricity to flower factories, plastic factories, and Merawi. As a solution to alleviate this problem and improve the reliability of the power system, enhancing the distribution system through solar-based distributed generation (DG) is studied. The proposed method is tested at R1-G3 66-bus feeder of Bahir Dar distribution system. The integration of DG decreases SAIDI from 1127.71 hr/cus.yr to 315.6 hr/cus.yr which reduces the power interruption duration by 72 %. The SAIFI decreases from 276.374 f/customer.yr to 88.32 f/customer.yr which reduces the power interruption frequency by 68% and this determines the reliability of the system that gives continuous service for its end-users which is 70 % reliability improvement. The EENS due to power interruption minimized from 5018.31MWh/yr to 1404.42 MWh/yr which is 3,613.89MWh/yr unutilized energy before installation of DG. The proposed solution is able to save 6,071,335.2 ETB per year from the unsold energy of one feeder R1-G3 only with 1.28 years payback period of investment. The PSO algorithm was used to locate the optimal sizing and placement of the DG. The algorithm has chosen buses 14, 22, and 59 to be used. These buses have capacities of 1.717, 1.467, and 1.147 MW, respectively. Keywords –Particle swarm optimization (PSO),optimal location, Distributed generation (DG),Electrical transient analyzerprogram(ETAP)