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Abstract
In the context of global response to climate change and promoting energy transformation, the rapid popularization of electric vehicles and the widespread application of clean energy have become important components of modern power systems. However, the charging demand of electric vehicles brings new challenges to regional power grids, especially those that rely on clean energy, due to its uncertainty and randomness. This study examines the impact of EV charging demand on the control efficiency of clean energy-based regional power grids. Using real grid data and time-series simulation, we develop a dispatch optimization framework incorporating a master-slave game model based on wind power output distribution. We simulate EV charging patterns, renewable fluctuations, and uncertainties in user behavior and station availability. The results show that unmanaged charging increases peak load by up to 20%, while optimized strategies like Time-of-Use (TOU) pricing, Direct Load Control (DLC), and Vehicle-to-Grid (V2G) reduce the peak-valley gap by 15%, improve renewable energy consumption by 12%, and lower curtailment. These findings offer valuable insights for EV integration and clean energy planning in regional grids. The results show that at a 30% EV penetration rate, the peak charging demand may lead to a 20% increase in the regional grid load, and by optimizing the charging time, the peak-valley load difference can be reduced by 15%. In addition, a reasonable charging strategy can help improve the utilization rate of clean energy, maximize the consumption of wind power and photovoltaic power generation, and reduce dependence on fossil fuel power generation.