杨康, 石璐杉, 周航, 王钊洋, 王博仑, 周霞, 唐昊. 含电动汽车集群的微电网多时间尺度优化调度[J]. 分布式能源, 2024, 9(3): 21-30. DOI: 10.16513/j.2096-2185.DE.2409303
引用本文: 杨康, 石璐杉, 周航, 王钊洋, 王博仑, 周霞, 唐昊. 含电动汽车集群的微电网多时间尺度优化调度[J]. 分布式能源, 2024, 9(3): 21-30. DOI: 10.16513/j.2096-2185.DE.2409303
YANG Kang, SHI Lu-shan, ZHOU Hang, WANG Zhao-yang, WANG Bo-lun, ZHOU Xia, TANG Hao. Multi-Time Scale Optimization Scheduling for Microgrids Containing Electric Vehicle Clusters[J]. Distributed Energy, 2024, 9(3): 21-30. DOI: 10.16513/j.2096-2185.DE.2409303
Citation: YANG Kang, SHI Lu-shan, ZHOU Hang, WANG Zhao-yang, WANG Bo-lun, ZHOU Xia, TANG Hao. Multi-Time Scale Optimization Scheduling for Microgrids Containing Electric Vehicle Clusters[J]. Distributed Energy, 2024, 9(3): 21-30. DOI: 10.16513/j.2096-2185.DE.2409303

含电动汽车集群的微电网多时间尺度优化调度

Multi-Time Scale Optimization Scheduling for Microgrids Containing Electric Vehicle Clusters

  • 摘要: 电动汽车放电时可作为电网的一种分布式储能装置,参与缓解高比例新能源接入微电网的供电压力。基于多时间尺度下分时电价的特点,提出一种考虑电动汽车集群的微电网多时间尺度优化调度方法。在日前调度阶段,基于分时电价对微电网内部储能、可中断负荷、可转移负荷等设备出力进行优化调度;在日内优化调度阶段,将电动汽车集群纳入到微电网能量调度中来,通过分析各电动汽车集群的调度潜力来实现合理的充放电。为验证所提方案的有效性,选取不同的用电峰平谷时段分时电价,让电动汽车集群参与微电网能量调度,结果证明考虑电动汽车集群参与的微电网多时间尺度优化调度能充分利用电动汽车集群的储能资源,提升微电网调度运行的灵活性和经济性。

     

    Abstract: When discharging, electric vehicles can serve as distributed energy storage units of the power grid to alleviate the power supply pressure of microgrids with high proportions of new energy integration. Capitalizing on the characteristics of time-of-use tariffs across multi-time scales, this study proposes a multi-time scale optimization scheduling method for microgrids that takes into account clusters of electric vehicles. In day-ahead scheduling phase, the equipment output such as internal energy storage, interruptible loads and transferable loads in the microgrid is optimized based on time of use tariffs; During intra-day optimization scheduling phase, electric vehicle clusters will be included in the energy scheduling of microgrids, and reasonable charging and discharging can be achieved by analyzing the scheduling potential of each electric vehicle cluster. To verify the effectiveness of the proposed scheme, electric vehicle clusters are selected to participate in microgrid energy scheduling based on variable time of use tariffs during peak, flat, and valley periods. The results show that the multi-time scale optimization scheduling for microgrids considering the participation of electric vehicle clusters can make full use of the energy storage resources of electric vehicle clusters and improve the flexibility and economy of microgrid scheduling operation.

     

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