Comprehensive Analysis and Optimization of Day-Ahead Scheduling: Influence of Wind Power Generation and Electric Vehicle Flexibility

With an increasing global emphasis on reducing carbon emissions and enhancing energy efficiency, the rising popularity of electric vehicles (EVs) has played a pivotal role in facilitating the transition to electrification within transportation sectors. However, the variability in their charging behavior has posed challenges for grid loads. In this study, a day-ahead scheduling model is developed for an integrated energy system to assess the impact of various electric vehicle charging modes on energy economics during typical days in summer, winter, and transition seasons. Additionally, the influence of optimized charging strategies on increasing the utilization of renewable energy and enhancing the operational efficiency of the grid is explored. The findings reveal that the abandonment rates of wind and solar energy associated with the orderly charging mode are 0 during typical days in winter and summer but decrease by 64.83% during the transition seasons. Furthermore, the power purchased from the grid declines by 18.79%, 19.34%, and 53.31% across these seasonal conditions, in respective. Consequently, the total load cost associated with the ordered charging mode decreases by 29.69%, 25.96%, and 43.71%, respectively, for summer, winter, and transition seasons.