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首页> 外文期刊>International Journal of Electrical Power & Energy Systems >Dynamic equivalent modeling of two-staged photovoltaic power station clusters based on dynamic affinity propagation clustering algorithm
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Dynamic equivalent modeling of two-staged photovoltaic power station clusters based on dynamic affinity propagation clustering algorithm

机译:基于动态亲和力传播聚类算法的二级光伏电站群动态等效建模

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摘要

This paper presents a novel dynamic clustering equivalent modeling method for a two-staged photovoltaic (PV) station cluster, which is a key tool to analyze the dynamic responses of the distribution network with high PV penetration. In this paper, a dynamic affinity propagation (DAP) clustering algorithm is proposed after studying the indexes that can describe the dynamic characteristics of two-staged PV power station. Then this algorithm is used to group the PV stations in the PV cluster according to their dynamic characteristics. Finally, the dynamic equivalent model of PV cluster is obtained by parameters aggregation of PV stations in the same group and simplification equivalent of the network. The proposed method is verified by a PV cluster distribution network with 20 two-staged PV stations and the simulation results show that the proposed dynamic equivalent model can accurately reflect the dynamic response characteristics of the PV cluster. At the same time, the simplified PV cluster model would reduce the computational complexity and the simulation time significantly. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文提出了一种新型的两阶段光伏电站集群动态聚类等效建模方法,它是分析具有较高光伏渗透率的配电网动态响应的关键工具。在研究可描述二级光伏电站动态特性的指标之后,提出了一种动态亲和力传播(DAP)聚类算法。然后使用该算法根据光伏集群中的光伏电站动态特性对光伏电站进行分组。最后,通过对同一组光伏电站的参数汇总和网络简化等效,得到光伏集群的动态等效模型。通过20个二级光伏电站的光伏集群配电网络对所提方法进行了验证,仿真结果表明,所提出的动态等效模型能够准确反映光伏集群的动态响应特性。同时,简化的PV群集模型将显着降低计算复杂度和仿真时间。 (C)2017 Elsevier Ltd.保留所有权利。

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