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All Journal Jurnal Teknologi Pendidikan VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Pengabdian Masyarakat Indonesia JURNAL TEKNOLOGI INFORMASI & KOMUNIKASI DALAM PENDIDIKAN Electron: Jurnal Ilmiah Teknik Elektro
Mega Silfia Dewy, Mega Silfia
Universitas Negeri Medan
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Optimasi Penempatan dan Penentuan Kapasitas Distributed Generator Menggunakan Cucko Search Algorithm untuk Mengurangi Rugi Daya Agnes Irene Silitonga; Simamora, Yoakim; S, Muhammada Aulia Rahman; Dewy, Mega Silfia; Silitonga, Agnes Irene; Ginting, Lisa Melvi
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 6 No 2: Jurnal Electron, November 2025
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v6i2.409

Abstract

Power losses in electrical distribution systems remain a major challenge that significantly impacts energy efficiency and system reliability. One promising approach to address this issue is the optimal placement and sizing of Distributed Generators (DGs) within the distribution network. This study aims to optimize DG placement and capacity using the Cuckoo Search Algorithm (CSA) and to compare its performance with several other algorithms, namely the Black Squirrel Optimization Algorithm (BSOA), Sine Cosine Algorithm (SCA), Teaching Learning Based Optimization - Grey Wolf Optimizer (TLBO-GWO), and GWO. The study was conducted on the IEEE 33-bus test system under two scenarios, with the initial condition of the distribution system exhibiting a power loss of 202.7 kW. In First Case Study, CSA achieved the lowest power loss of 105.31 kW, corresponding to a 48.05% reduction. In contrast, BSOA and TLBO-GWO reduced losses to 116.67 kW (42.44%) and 128.46 kW (36.62%) respectively. In Second Case Study, CSA again demonstrated superior performance with a loss reduction of 56.66%, outperforming SCA (56.33%), BSOA (55.97%), and GWO (55.82%). The optimal DG placement and sizing significantly improved overall system efficiency. The results indicate that CSA possesses strong exploration and convergence capabilities in identifying optimal DG configurations. Its application enables greater reduction in power losses while also enhancing voltage profiles and system stability. These findings suggest that CSA is an effective and competitive method for power distribution optimization involving distributed generation
Co-Authors Agnes Irene Silitonga Ali Akbar Lubis Annisa, Selly Bakti Dwi Waluyo Dadang Mulyana, Dadang Erita Astrid Ganefri . Hutahaean, Harvei Desmon Imannuel, Michael Fritz Immanuel, Michael Fritz Immanuel, Michel Frits Indrati Kusumaningrum Lisa Melvi Ginting Muhammad Dani Solihin Muhammad Isnaini Muhammad Isnaini S, Muhammada Aulia Rahman Sembiring, Muhammad Aulia Rahman Silitinga, Agnes Irene Yoakim Simamora Yoakim Simamora