CD Skripsi
Rekonfigurasi Jaringan Distribusi Dengan Metode Breeder Algoritma Genetika (Bga)
Nowadays, population growth is growing very rapidly following the economic growth. This also has an impact on the increasing demand for electricity. The continuous increase in electrical load can affect the quality of electric power obtained by consumers. The quality of this voltage is influenced by power losses and voltage drops. This study will try to overcome the problem using a new method, namely Breeder Genetic Algorithm (BGA) which is inspired by the concept of animal recovery with the strategy "mating two individuals with high fitness is more likely to produce offspring with high fitness than mating two individuals selected at random". The BGA method can solve the problem of chromosomes trapped in the local optimum solution region and cause BGA to converge faster than ordinary GA. This BGA method will be applied to the IEEE 33 bus radial distribution system using Matlab software and ETAP software so that it is in accordance with the provisions of SPLN no.72 of 1987 which does not exceed +5% and -10%.The results obtained are:reconfiguration using Etap software resulted in active power loss (P) decreased from 211kW to 111.8kW and reactive power loss (Q) decreased from 143.1kVar to 80.3kVar. After validating the results with manual calculations using Microsoft Excel, the active power loss (P) is 121.6kW and reactive power loss (Q) is 75.8kVar. In addition, the average improvement in voltage drops from5,4690% to2,7784%.The results of the reconfiguration using the BGA method get a better value of power loss and voltage drop than before the reconfiguration.
Keywords: BGA, network distribution, ETAP, Matlab, reconfiguration
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