基于电动汽车充电站的不平衡配电网自愈及优化运行OA北大核心CSTPCD
Self-healing and Optimal Operation of Unbalanced Distribution Network Based on Electric Vehicle Charging Station
分布式电源和电动汽车大量接入配电网,打破了配电网的三相平衡状态,致使传统的配电网保护方案无法适应时代的发展需求.为此,在现有平衡系统故障恢复策略的基础上,提出了一种基于电动汽车充电站的不平衡配电网灾后两阶段故障恢复策略.第一阶段以故障恢复成本最小为目标确定故障后的孤岛运行方案.第二阶段综合考虑电动汽车充电站及各分布式电源机组的折旧、运维、弃负荷惩罚等成本,以配电网运行收益最大为目标建立协同优化模型,以确定故障时各充电站出力情况.最后通过改进的IEEE 33节点系统验证所提两阶段故障自愈模型及优化运行策略的有效性.结果表明,所提方法较传统的孤岛划分法弃负荷率更低,为解决不平衡配电网的故障恢复问题提供了新思路.
The three-phase equilibrium state of a distribution network is broken owing to the large number of distributed power sources and electric vehicles connected to the distribution network,resulting in the traditional distribution network protection scheme illegally adapting to current development needs. Therefore,this study presents a two-stage fault recovery method for imbalanced distribution networks based on electric vehicle charging stations using an existing balancing system fault recovery technique. The island operation strategy after the fault is determined in the first stage to reduce the fault-recovery cost. In the second stage,a collaborative optimization model is established to determine the output of each charging station when a fault occurs,with the goal of maximizing the operating income of the distribution network,considering the cost of depreciation,operation and maintenance,and the load abandonment penalty of electric vehicle charging stations and distributed generation units. Finally,the enhanced IEEE 33 node system validates the effectiveness of the two-stage fault self-healing model and the optimal operating method suggested in this study. The results reveal that the proposed technique has a lower load rejection rate than the classic island division method,thereby providing a novel solution to the fault-recovery problem of an imbalanced distribution network.
李英量;白博旭;朱琦;杨一;李飞
西安石油大学电子工程学院,西安市 710065
动力与电气工程
故障恢复孤岛划分电动汽车不平衡配电网
fault recoveryisland partitionelectric vehiclesunbalanced distribution network
《电力建设》 2024 (006)
37-46 / 10
国家自然科学基金企业创新发展联合基金重点项目(U20B2029);国家重点研发计划项目(2023YFC2810902);陕西省科技厅面上项目(2024JC-YBMS-405) This work is supported by the Key Project of Enterprise Innovation and Development Joint Fund by National Natural Science Foundation of China(No.U20B2029),the Key Research and Development Program of China(No.2023YFC2810902)and Natural Science Basic Research Program of Shaanxi(No.2024JC-YBMS-405).
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