Simulating microgrids that incorporate electric vehicles and photovoltaic solar energy, along with their penetration levels, is a complex task that requires considering realistic grid parameters. This study presents an integrated simulation method using Python and OpenDSS, enabling researchers to analyze factors such as load curves, communication links, electric vehicle demand, photovoltaic generation, electric vehicle penetration levels, and connection event probability curves. Additionally, the software includes smoothing algorithms for solar radiation to mitigate voltage fluctuations. The simulation tool also allows for the evaluation of communication delays between the system aggregator and charging stations
when modifying the charging setpoint at customer connection bars. The results indicate that communication delays significantly impact voltage stability at consumer connection points. Smoothing algorithms, such as the Savitzky-Golay filter, reduce voltage fluctuations by up to 8% in high PV penetration scenarios. Moreover, PV penetration levels around 0.6 were found to create the highest transformer loads, highlighting the need for adaptive control strategies. Voltage deviations at customer loads ranged from +1.5% to −3.2% depending on the delay time and PV penetration.
