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Study on Power Loss Minimization for Distribution Network Reconfiguration Using Genetic Algorithm Case Study: Addis North 132/15 KV Substation

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dc.contributor.advisor Kiros, Tesfaye (Mr.)
dc.contributor.author Habtamu, Eshete
dc.date.accessioned 2018-09-21T12:07:05Z
dc.date.available 2018-09-21T12:07:05Z
dc.date.issued 2018-06
dc.identifier.uri http://etd.aau.edu.et/handle/123456789/12092
dc.description.abstract Distribution system is a largest portion of network of electrical power system. Different actions have been taken to improve the efficiency of the distribution network. One of the most basic and the commonest way to improve the performance of the distribution network is the network reconfiguration. Electric distribution systems reconfiguration comprises tie and sectionalizing switches. Tie switches are normally open, and sectionalizing switches are normally closed. By opening and closing these switches, the distribution network can be reconfigured. This reconfiguration can be done for the objective of loss minimization. In order to get feasible results (loss minimization), the reconfiguration must meet some constraints, like Kirchhoff‟s voltage and current laws, other equality and inequality constraints. Distribution network reconfiguration is an optimization problem and needs a suitable algorithm (method).The method used for this optimization problem is a genetic algorithm optimization method. The genetic algorithm has been described in detail and then applied specifically to the network reconfiguration problem. In the optimization process, load flow of the distribution system was computed. Then, computer simulation was performed by using DIgSILENT PowerFactory software for analyzing the distribution network reconfiguration. In addition, optimized genetic algorithm was used as a tool for network reconfiguration. Addis North 132/15 kV substation feeders are used as test system for this particular study. Before the reconfiguration, the power loss is 3.983783 MW, after reconfiguration the power loss has decreased from 3.983783 MW to 1.594640 MW, which is 2.389143 MW (59.91716%) reduction. Besides, the maximum voltage drop before reconfiguration is 0.352639, and the reconfiguration increased it to 5.050102. The minimum voltage before reconfiguration is 0.992618 p.u., and the minimum voltage is found to be 0.947288 p.u. after reconfiguration. In addition, the maximum voltage before reconfiguration is 0.992069 p.u., and it is found to be 0.9953500 p.u. after reconfiguration. Based on the findings of this research, it is concluded that reconfiguration of distribution networks can reduce power loss and operating cost as well as improves the voltage profile of distribution systems. Hence, it is recommended that all the distribution network feeders of Addis Ababa city to be reconfigured for the betterment of the Ethiopian Electric Utility (EEU) services. en_US
dc.language.iso en_US en_US
dc.publisher AAU en_US
dc.subject Network Reconfiguration en_US
dc.subject Genetic Algorithm Optimization en_US
dc.subject Power Loss Minimization en_US
dc.title Study on Power Loss Minimization for Distribution Network Reconfiguration Using Genetic Algorithm Case Study: Addis North 132/15 KV Substation en_US
dc.type Thesis en_US

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