<![CDATA[Distributed generation (DG) ha s emerged as an effective solution for improving power quality, enhancing voltage profiles, and reducing power losses in electrical distribution systems. This study investigates the impact of renewable-energy-based DG integration on the voltage profile and power losses of the Unsyiah distribution feeder in Banda Aceh, Indonesia. The distribution network was modeled and analyzed using ETAP 16.0.2, while MATLAB R2021a with the backpropagation artificial neural network (ANN) method was employed to estimate solar radiation intensity and wind speed data for photovoltaic (PV) and wind power plant (WPP) generation. The ANN model was trained using environmental and climate data, producing regression values of 0.84901 for solar radiation prediction and 0.85083 for wind speed prediction, indicating satisfactory predictive performance. Two DG placement scenarios with a penetration level of 20% of the total feeder load (388.4 kW) were evaluated at Bus USK 01 and Bus USK 24. Simulation results demonstrate that DG integration significantly improves the voltage profile, particularly at buses located near the end of the feeder where voltage drops are more severe. The optimal scenario was achieved by placing wind-power-based DG at Bus USK 24, which reduced active power losses from 11.8 kW to 8.1 kW and reactive power losses from 13.1 kVAR to 8.6 kVAR. Overall, the integration reduced active power losses by 31.35% and reactive power losses by 34.35%. The findings confirm that both DG placement location and DG type strongly influence the effectiveness of voltage profile enhancement and power loss reduction in radial distribution systems.]]>
