Research Article
Optimal Allocation of Renewable Distributed Generations Using Sensitivity Analysis and PSO
@INPROCEEDINGS{10.4108/eai.30-8-2021.2311533, author={Sugiarto Sugiarto and Oni Yuliani}, title={Optimal Allocation of Renewable Distributed Generations Using Sensitivity Analysis and PSO}, proceedings={Proceedings of the 2nd International Conference on Industrial and Technology and Information Design, ICITID 2021, 30 August 2021, Yogyakarta, Indonesia}, publisher={EAI}, proceedings_a={ICITID}, year={2021}, month={10}, keywords={sensitivity distribution network distributed generation}, doi={10.4108/eai.30-8-2021.2311533} }- Sugiarto Sugiarto
Oni Yuliani
Year: 2021
Optimal Allocation of Renewable Distributed Generations Using Sensitivity Analysis and PSO
ICITID
EAI
DOI: 10.4108/eai.30-8-2021.2311533
Abstract
A growing demand for electricity, along with a scarcity of available producing capacity, has fueled the growth of Renewable Distributed Generation (RDG), which includes wind, solar, and hydroelectric sources of energy. Abstract: The location of DG sources has a significant effect on the amount of system losses that occur in the distribution network. This study discusses the identification of the most suitable placement for the IEEE 30 Bus Test System to reduce power loss while simultaneously improving voltage deviation. It is necessary to utilize Sensitivity Analysis to determine the placement of DGs in the network, while Particle Swarm Optimization is used as the optimization method to determine the size of DGs in the network in order to minimize the power losses of the system. The findings demonstrate that the installation of three DGs is beneficial in minimizing power loss and voltage variation.