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

Author

Listed:
  • Guocheng Li

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Cong Wang

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Jian Zheng

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Zeguang Lu

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Zhongmei Zhao

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Jinglan Cui

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Shaocong Bi

    (State Grid Shandong Electric Power Company, Dezhou Power Supply Branch, Dezhou 253000, China)

  • Xinyu Gao

    (Institute of the Building Environment & Sustainability Technology, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Xiaohu Yang

    (Institute of the Building Environment & Sustainability Technology, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

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.

Suggested Citation

  • Guocheng Li & Cong Wang & Jian Zheng & Zeguang Lu & Zhongmei Zhao & Jinglan Cui & Shaocong Bi & Xinyu Gao & Xiaohu Yang, 2025. "Comprehensive Analysis and Optimization of Day-Ahead Scheduling: Influence of Wind Power Generation and Electric Vehicle Flexibility," Energies, MDPI, vol. 18(7), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1639-:d:1619801
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    References listed on IDEAS

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