Within distributed generation (DG), different types of technology are used to produce electricity, including photovoltaic and wind generation systems. However, their coupling in large quantities can cause power quality problems due to the stochasticity of the data in the distribution circuits; therefore, the main objective of this article is to analyze, through simulation, the impact of coupling microgeneration or distributed generation. The system used is the Zonhan 600 W/24 V DC wind turbine and 230 Wp polycrystalline solar panels, both known for their high efficiency. Meteorological data is obtained from an LSI LASTEM station equipped with a DNA121, DMA672.1 optoelectronic anemometer, and an ELOG305 data logger, which is coupled to an NI cRIO9022. The data is then entered into an OPAL5600 (Real-Time Digital Simulator). Simulink—DigSilent is loaded inside the Opal and experimentally verified using the Fluke 434 Power Quality Analyzer. The system used is the Zonhan 600 W/24 V DC wind turbine and 230 Wp polycrystalline solar panels, with meteorological data obtained from an LSI LASTEM station with DNA121, DMA672.1 optoelectronic anemometer and an ELOG305 data logger coupled to NI cRIO9022, enter the data to OPAL5600 (Real-Time Digital Simulator). Simulink—DigSilent is loaded inside the Opal and experimentally verified using the Fluke 434 Power Quality Analyzer. The energy demand data is taken from the monthly records of the higher education institution. According to the results, the impact of the DG system is less than 1%, but if it increases by 25%, it begins to generate an effect of 5.68% on the network. In the case of the total harmonic distortion (THD), the result is 3.7%, well below the allowed value of 8%, and finally, the power factor value is 0.98, exceeding the minimum acceptable value of 0.92 according to the normative. Therefore, the DG system does not impact the low voltage network at small scales, being considered only self-consumption.