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作 者:杨宝 Bao Yang(Business School,University of Shanghai for Science and Technology,Shanghai)
机构地区:[1]上海理工大学管理学院,上海
出 处:《建模与仿真》2024年第6期6404-6415,共12页Modeling and Simulation
摘 要:随着电动汽车的迅速发展,人们对微电网负荷压力的关注也愈发凸显。在此背景下,共享充电桩的灵活运用成为解决电动汽车无序充电导致电网负荷增加问题的重要途径。本文提出利用自动驾驶技术对电动汽车进行调度优化,以缓解电网压力。首先,利用自动驾驶技术在规定时间内实现电动汽车进桩和离桩,最大化充电桩资源利用,实现有序充放电,缓解电网负荷。其次,采用自适应遗传算法实现有序充电调度优化,提升了电网运行效率和稳定性。最后本文分别通过改变电动汽车充放电需求、最终电量要求,以及共享充电桩和电动汽车数量进行调度优化,在满足电动汽车充电需求和缓解微电网压力的同时,分析各情况下的趋势变化,为未来更多电动汽车参与电网充电提供重要的理论和实践意义。With the rapid development of electric vehicles,concerns about load pressure on microgrids have become more prominent.In this background,the flexible use of shared charging piles has become an important way to solve the problem of increased grid load due to disordered charging of electric ve-hicles.This paper proposes scheduling optimization of electric vehicles using autonomous driving techniques to relieve pressure on the power grid.First,using automatic driving technology to achieve electric vehicles entering and leaving piles within the specified time,maximizing the use of charging pile resources,achieving orderly charging and discharging,and alleviating the load on the power grid.Secondly,an adaptive genetic algorithm is used for scheduling optimization to improve the efficiency and stability of power grid operation.Finally,this paper provides scheduling optimization by changes in EV charging and discharging requirements,final power requirements,and the number of shared charging piles and EVs,while satisfying EV charging requirements and relieving the pressure on the microgrid,the trend changes in each case are analyzed to provide important theoretical and practical implications for more EVs to participate in grid charging in the future.
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