Electrical Computer Engineering

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    OPTIMAL PLACEMENT OF SOLAR DISTRIBUTED GENERATION FOR RELIABILITY IMPROVEMENT IN DISTRIBUTION NETWORKS USING WHALE OPTIMIZATION ALGORITHM (CASE STUDY: BISHOFTU SUBSTATION 2
    (Hawassa University, 2025-05-12) HIKMA NUREDIN
    The power distribution system in Bishoftu, Ethiopia, is faced with significant reliability challenges, including frequent interruptions, overloading, and poor performance that fall below national standards. These issues are caused by increasing load demand and inefficient system management. To address these challenges, the integration of solar-based distributed generation (DG) was investigated as a solution to enhance the reliability of the Bishoftu Substation. The K9 feeder, which exhibits the most severe reliability issues, was selected for this study, with initial reliability indices of SAIFI = 363.5 interruptions/customer/year and SAIDI = 803.14 hours/customer/year, far exceeding the national standards of SAIFI = 20 and SAIDI = 25. The Whale Optimization Algorithm (WOA) was utilized in MATLAB to determine the optimal sizing and placement of DG units, with the aim of minimizing SAIFI and SAIDI. Solar energy was identified as the most viable DG option based on local solar irradiance data. Significant improvements were demonstrated through optimization, with SAIFI and SAIDI reduced by up to 86% and 87% respectively, achieving values of SAIFI = 50.89 interruptions/customer/year and SAIDI = 104.4 hours/customer/year. An economic analysis was also conducted to evaluate the initial investment and life cycle costs, ensuring the feasibility of the proposed solution. It was concluded that the integration of optimally sized and placed solar DG units can drastically improve system reliability, reduce interruptions.
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    STUDY THE IMPACT OF DISTRIBUTED GENERATION ON THE RELIABILITY OF LOCAL DISTRIBUTION SYSTEM (Case study: Motta Distribution Substation)
    (Hawassa University, 2020-10-28) Bimrew Mhari Enyew
    Electric distribution system power quality is a rising concern. Customers require higher quality service due to more sensitive electrical and electronic equipment‟s, and effectiveness of a power distribution system is measured in terms of efficiency, service continuity or reliability, service quality in terms of voltage profile and stability and power distribution system performance. The present Motta distribution substation has encountered frequent power interruptions and power quality problems. The interruptions are caused mainly by Permanent Short circuit (PSC), Transient Earth fault (TEF). There are also planned outages for operation and maintenance purpose. The substation‟s System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) are 806 and 1,394.145, respectively. The substation is not reliable by the standard of Ethiopian Electric Agency (EEA) which set (SAIFI =20 and SAIDI= 25). This reliability gap calls for searching of effective methods for improving the reliability of the distribution system. This thesis presents impact of DG on reliability assessment at Motta distribution substation of 230/33 transformer two 33 kV radial outgoing feeders distribution and the base case reliability analysis using Monte Carlo and analytical enumeration system and has high loss of money that is 0.438 M$/a and 0.444 M$/a respectively for utility but Monte Carlo analysis is better than that of Analytical Enumeration. The improved reliable power distribution is due to the use of proper size and site of DG at the low voltage profile value bus of the distribution system by using probabilistic Monte Carlo simulation of reliability analysis and that of Enumeration analysis of the system using DIgSILENT power factory software. The NPC of DG is 20,831,473.21$ which optimized using HOMER software at the required size and the reliability of the distribution system is improved after the use of DG that is reducing SAIFI, CAIFI by 97.8%, and SAIDI by 76%, increasing ASAI by 14.38% and reducing ASUI by 76% and reducing the total power loss to 0.32 MW. The cost analysis is done on this thesis by using the Monte Carlo reliability analysis output and the DG total net present cost (TNPC) so the payback period is less than five years that is 4.28 years which means that the project is profitable