Bayesian Network Governance of Electric Vehicle Charging Pile Disordered Charging Load Impacts on the Grid

In order to solve the adverse effects of uncontrolled charging of electric vehicles on the distribution network, the study constructs a Monte Carlo-based uncontrolled charging load model to calculate the effects of uncontrolled charging on the electric vehicle side on the distribution network load and voltage.Based on this, the electric vehicle trip chain is modeled by Bayesian network so as to manage the charging options of electric vehicles.The charging loads of EVs managed by the Bayesian network at different sizes and different charging locations are predicted to explore the impact of the Bayesian network on EV charging and distribution grid loads.The peak weekday grid base load occurs at 11:00 AM (3695 kW) and 20:00 PM (3656 kW).On weekdays, the grid base load occurs at 12:00 pm (3495 kW) and 20:00 pm (3725 kW), and the peak load increases significantly with the increase of penetration rate and the time is gradually advanced.The end node 18 has the lowest voltage and the lowest value of voltage at node 18 is 0.9135 and 0.9140 on weekdays and bi-weekdays respectively when only the base load is present.At 100% penetration, the minimum voltage is 0.9015 and 0.9008 on weekdays and bi-weekdays, respectively.When the penetration rate of electric vehicles is 20% and 30%, the average value of peak load of electric vehicle charging power increases to 150.05kW and 220.85kW.When the charging scheme of residential charging + office charging is used, the peak load of EV charging in residential areas is reduced by 60.3%.