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Vector-variable based modeling method for large-scale wind farm considering collector system dynamics.

Authors :
Lin, Siqi
Yao, Wei
Zhao, Yifan
Shi, Zhongtuo
Peng, Li
Cheng, Yu
Ai, Xiaomeng
Wen, Jinyu
Source :
International Journal of Electrical Power & Energy Systems. Jul2023, Vol. 149, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Different from conventional power plants, a wind farm usually consists of hundreds of wind generators and collector systems with arbitrary topology. The numerous devices increase modeling efforts and computational burden. This paper proposes a vector-variable based method for dynamic modeling of the large-scale wind farm considering collector system dynamics. Using the vector variables, the modeling method converts the complex wind farm containing many components to a model consisting of two typical submodules, the wind generator module and the collector system module. These submodules can establish any number of wind generators and any topology of the collection systems considering dynamics freely, with good scalability. The correctness and high simulation efficiency of the established model are validated by the electromagnetic model. Furthermore, a detailed wind farm containing twenty-five wind generators is built via the proposed method. Compared with the aggregation model, the results show that the established model can reflect the wind farm stability accurately. Also, by comparing with the model neglecting the collector system dynamics, the results reveal the relative error caused by neglecting the collector system dynamics can lead to misjudgment of instability mode when analyzing the sub-synchronous modes. [Display omitted] • Based on vector variables, two typical modules can model whole wind farm in detail. • The model has better scalability and higher efficiency than electromagnetic model. • The model can reveal dynamics of wind farm more precise than aggregation model. • Neglecting collector network dynamics will cause misjudgement of instability mode. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01420615
Volume :
149
Database :
Academic Search Index
Journal :
International Journal of Electrical Power & Energy Systems
Publication Type :
Academic Journal
Accession number :
162396364
Full Text :
https://doi.org/10.1016/j.ijepes.2023.109016