邓衍辉, 李剑, 卢国强, 王怀远. 考虑分区域动态电价机制引导的电动汽车充电优化策略[J]. 电力系统保护与控制, 2024, 52(7): 33-44. DOI: 10.19783/j.cnki.pspc.230931
引用本文: 邓衍辉, 李剑, 卢国强, 王怀远. 考虑分区域动态电价机制引导的电动汽车充电优化策略[J]. 电力系统保护与控制, 2024, 52(7): 33-44. DOI: 10.19783/j.cnki.pspc.230931
DENG Yanhui, LI Jian, LU Guoqiang, WANG Huaiyuan. Charging optimization strategy of electric vehicles guided by the dynamic tariff mechanism of a subregion[J]. Power System Protection and Control, 2024, 52(7): 33-44. DOI: 10.19783/j.cnki.pspc.230931
Citation: DENG Yanhui, LI Jian, LU Guoqiang, WANG Huaiyuan. Charging optimization strategy of electric vehicles guided by the dynamic tariff mechanism of a subregion[J]. Power System Protection and Control, 2024, 52(7): 33-44. DOI: 10.19783/j.cnki.pspc.230931

考虑分区域动态电价机制引导的电动汽车充电优化策略

Charging optimization strategy of electric vehicles guided by the dynamic tariff mechanism of a subregion

  • 摘要: 为应对大规模电动汽车无序充电引起的配电网运行损耗增加问题,提出一种分区域动态电价机制引导的电动汽车(electric vehicle,EV)充电优化策略。该动态电价机制是根据不同区域内的负荷特点建立不同的动态电价,从而优化对应区域的EV充电。其中商业区建立计及充电站充电总功率的动态电价模型,居民区和办公区采用计及风光出力的动态电价模型。同时,提出充电效益系数模型以提升在居民区和办公区用户的充电时间满意度。最后,在IEEE33节点系统上进行仿真验证。结果表明,所提出的基于分区域动态电价机制的EV充电优化策略能够在保证车主利益的同时,降低网损、提高配网电压质量、促进风光消纳以及提升配网的经济性。

     

    Abstract: To deal with the problem of the increasing operating loss of a distribution network caused by the disorderly large-scale charging of electric vehicles(EVs), a charging optimization strategy guided by the dynamic tariff mechanism of a subregion is proposed. The dynamic electricity price mechanism is to establish different dynamic electricity prices according to the load characteristics in different regions to optimize EV charging in the corresponding regions. The dynamic electricity price model taking into account the total charging power of the charging station is established in the commercial area, and the dynamic electricity price model taking into account wind and photovoltaic power output is adopted in residential and office areas. A charging benefit coefficient model is proposed to improve the charging time satisfaction of users in residential and office areas. Finally, the simulation results on the IEEE33-node system show that the EV charging optimization strategy proposed can not only guarantee the interests of the car owners, but also reduce network loss, improve the voltage quality of the distribution network, promote wind and photovoltaic power consumption,and enhance the economy of the distribution network.

     

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