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International Journal of Electrical Power & Energy Systems
Article . 2018 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Dynamic equivalent modeling of two-staged photovoltaic power station clusters based on dynamic affinity propagation clustering algorithm

Authors: Peixin Li; Wei Gu; Liufang Wang; Bin Xu; Ming Wu; Wanxing Shen;

Dynamic equivalent modeling of two-staged photovoltaic power station clusters based on dynamic affinity propagation clustering algorithm

Abstract

Abstract 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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
43
Top 10%
Top 10%
Top 10%
gold