With the rapid proliferation of electric vehicles

their charging loads pose new challenges to power grid stability and operational effi-ciency. To address this

this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province

leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods

with significant load fluctuations exerting substantial pressure on the grid. In response

this paper proposes strategic interventions including optimized charging infrastructure planning

time-of-use electricity pricing mechanisms

and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting

smart grid dispatching

and vehicle-grid integration

thereby enhancing grid operational efficiency and sustainability.