Open AccessOPTIMASI PENEMPATAN DISTRIBUTED GENERATOR TERHADAP PERBAIKAN PROFILE TEGANGAN PADA PENYULANG ABANG MENGGUNAKAN METODE QUANTUM GENETIC ALGORITHM (QGA)
Author(s) -
Dewa Gede Satria Bayu Putra,
Antonius Ibi Weking,
Wahyu Setiawan
Publication year - 2018
Publication title -
jurnal spektrum
Language(s) - English
Resource type - Journals
eISSN - 2302-3163
pISSN - 2684-9186
DOI - 10.24843/spektrum.2018.v05.i02.p39
Subject(s) - matlab , generator (circuit theory) , voltage , quantum , algorithm , voltage drop , genetic algorithm , computer science , control theory (sociology) , mathematics , electrical engineering , physics , engineering , mathematical optimization , artificial intelligence , quantum mechanics , power (physics) , control (management) , operating system
This research aims to optimize the Distributed Generator (DG) placement to improve the voltage magnitude on the Abang Feeder. The percentage of voltage drop received at the end of the load according to PLN is a maximum of 10% below the nominal voltage of a feeder. This study uses the MATLAB application with the Quantum Genetic Algorithm (QGA) method. The QGA method is an evolution of the Genetic Algorithm method which is combined with quantum calculations. This QGA method is combined with Newton Raphson's theory. The results obtained from this study are the placement of DGs in several buses on the broiler feeder and the improvement of the voltage magnitude that was previously not in accordance with standards ( below 18 kV or 0,9 p.u ) to be better ( 20 kV or 1 p.u and not more than 21 kV or 1,05 p.u ) and has met the predetermined standards.