Electrical Computer Engineering

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    DISTRIBUTION SYSTEM RELIABILITY IMPROVEMENT USING DISTRIBUTED GENERATION AND NETWORK RECONFIGURATION
    (Hawassa University, 2021-10-28) MEKLIT GIRMA
    Power supply reliability is the basic issue for economic and technology development of the country. The sufficient or adequate and secure supply of power will assure the reliability of the system. Unreliability of the system occur due to high outage frequency and duration, system overload and unsecure system or protection system. When the distribution system is reliable, it has capacity to meet the demand of customer and operate under adverse condition. Arbaminch distribution system has encountered frequent power interruption and power quality problem. The interruptions are mainly caused by system overload and short circuit fault. The reliability of the distribution system is assessed based on the data from Ethiopian Electric Power Corporation. Arbaminich substation of feeder -05 is selected as case study, which has high rate of interruption. Feeder -05 has SAIDI value of 236.8386 Hr./cust. /yr. and SAIFI of 221.6338 f/cust. /yr. The reliability indexes values of feeder -05 are not within the ranges of bench marks of reliability requirement. This thesis focused on reliability improvement of distribution system with better placement of distributed generation and network reconfiguration. Particle swarm optimization algorithm is used for placement of DG, size and network reconfiguration. The algorithm is done using MATLAB 2016 software. Based on the availability in the area, efficiency, cost and emission level, Solar and Microturbine sources are used as distributed generation. The suitable site and size of DG are found at bus 10 with suitable size 4.5 MW. For network reconfiguration sectionalizing switch is used. Before reconfiguration the switch was placed at bus 20, 21, 22,23 and 24. During network reconfiguration switch changed to bus 3, 4,12,24 and 31. The reliability indices SAFI, SAIDI and EENS value improved by 82.81%,78.89% and 78.10% respectively after DG with reconfiguration used. Expected interruption cost before applying the proposed method is 9,758,852$ /year. After the proposed method used expected interruption cost reduced to 2,995,270$ /year. This indicates that, 6,763,582 $/year is saved after using the proposed techniques
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    Power Loss Reduction and Voltage Profile Improvement of Distribution Feeder (Case study: Hawassa Substation Distribution Feeder 7)
    (Hawassa University, 2021-12-22) Tigist Taye
    Power quality issues, mainly voltage sag, are the major problem inside the distribution network. Further, losses also create serious concerns in the power distribution. As a result, in this work, capacitors are optimally placed using the Genetic Algorithm (GA) to mitigate voltage sag and power losses. A practical data set from Hawassa substation, which has nine 15kV outgoing feeders and four 33kV outgoing feeders, is being utilized to show the implementation of the proposed work. From those 15kV outgoing lines, feeders 7, 5, 8, 4, 3, 6, 2, 9 and 1 have high power loss and voltage drop respectively from load flow results. Feeder 7 is selected from this work due to its high power loss compared to the rest of the feeder by load flow analysis. This feeder has been modeled in ETAP software and Newton Raphson load flow is performed. From load flow simulation of feeder 7, it has been seen that the feeder has a power loss of 0.472MW. The objective function of this thesis work is to minimize power loss, improve voltage profile and power factor with minimum investment cost. This is achieved by optimal capacitor placement for reactive power compensation of the network. The operation of the capacitor bank is done by the CQ930 automatic capacitor controller, which provides a reliable method of monitoring and switching. By using GA, the power loss is improved from 0.472MW to 0.276MW, the minimum voltage magnitude is improved from 90.24% to 95.62%, and the power factor is improved from 87.35% to 90.49%, and finally, the system capacity is increased from 2.612MVA to 3.152MVA. Due to this overall improvement in the network, EEU can save $39,707.22 while the total investment cost is 63,200 with a payback period of seven months