@thesis{thesis,
		author={Febrianto Wijanarko  Rahmat and SALIM KHAMIM  MUHAMMAD and Satya Dini  Hasna},
		title ={OPTIMASI PENEMPATAN DAN KAPASITAS DISTRIBUTED GENERATION PADA PENYULANG KALINGGA MENGGUNAKAN METODE GENETIC ALGORITHM},
		year={2022},
		url={http://156.67.221.169/5381/},
		abstract={The increment of electricity distribution load affects the value of power system losses and
system voltage profile. Power system losses tend to get higher as the load increase while
voltage profile deviation from the nominal value becomes larger. The power loss in
Kalingga Feeder is 3.82% of the power generation, making it necessary to have a
mitigation plan to overcome the losses issue. Installation of Distributed Generation is a
way to mitigate the power losses in the distribution system. Determining Distributed
Generation location and capacity can be done using the Genetic Algorithm method.
Based on the results of optimization using the genetic algorithm method, the optimum
value of Distributed Generation shall be installed in bus 11 (2.86MW), bus 21 (2.83MW)
and bus 26 (2.89MW). The installation of Distributed Generation on the Kalingga Feeder
has successfully reduced the power loss to 1.04%. The maximum and minimum voltage
profiles can be maintained between 18.70 kV to 19.30kV.}
		}