基于聚类思想的配电网电动汽车优化调度研究

Zhijian Liu, Zizhuo Wang, Pengcheng Li, Jing Dai, Jikai Chen, Zhi-ying Xu, Yunxu Tao
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引用次数: 0

摘要

本文针对电动汽车的充放电功率进行了以下研究。首先,在综合考虑电动汽车充放电特性的基础上,采用聚类方法对大量电动汽车进行集成;其次,求解电动汽车集群各时刻充放电功率约束和电池容量约束,构造电动汽车集群边界条件;然后,构建以负荷波动最小为目标的优化模型,对集群各时刻的电力状况进行优化。最后,基于IEEE 33节点系统进行了仿真工作,验证了所提聚类优化方法的有效性。仿真结果表明,该方法能够合理分配电动汽车集群每次的总充放电功率,从而达到平滑电网负荷曲线、提高电网运行经济性的目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Optimal Scheduling of Electric Vehicles in Distribute Network Based on Cluster Thought
In this paper makes the following research aiming at the charging and discharging power of electric vehicles(EVs). Firstly, a large number of EVs are integrated by means of clustering based on a comprehensive consideration of EV charging-discharging characteristics. Second, the EV cluster charging-discharging power and battery capacity constraints at each moment are solved and the EV cluster boundary conditions are constructed. After that, an optimization model with the objective of minimizing load fluctuation is constructed to optimize the power situation of the cluster at each moment. Finally, simulation work is carried out based on the IEEE 33-node system to verify the effectiveness of the proposed cluster optimization method. The simulation results show that the proposed method can reasonably allocate the total charging-discharging power of the EV cluster at each time, and then achieve the purpose of smoothing the grid load curve and improving the grid operation economy.
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