Dynamic Clustering and Operation Evaluation of Renewable Energy Station

Junsong Yu; Heyan Huang; Yaohui Xiao; Weifeng Ding; Jie Li; Hanxuan Liu

doi:10.1109/EI259745.2023.10513132

Dynamic Clustering and Operation Evaluation of Renewable Energy Station

Junsong Yu
, Heyan Huang
, Yaohui Xiao
, Weifeng Ding
, Jie Li
, Hanxuan Liu

Operation Monitoring Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Aiming at the difference of dynamic characteristics about doubly-fed wind turbines and the complexity of equivalence problems, a multi-machine dynamic equivalence model for wind farms based on improved K-means algorithm is proposed. Considering the input wind speed and the different state parameters of the units, several indexes are selected to dynamically group the units in the wind farm. Based on the clustering results, the proposed wind farm's equivalent model is established in MATLAB/Simulink. According to the simulation results, the multi-machine equivalent model has higher accuracy and better application effect than the single-machine equivalent model, which can more effectively depict the grid-connected characteristics and operational state of doubly-fed wind farms.

Original language	English
Title of host publication	2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4176-4181
Number of pages	6
ISBN (Electronic)	9798350345094
DOIs	https://doi.org/10.1109/EI259745.2023.10513132
Publication status	Published - 2023
Externally published	Yes
Event	7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023 - Hangzhou, China Duration: 15 Dec 2023 → 18 Dec 2023

Publication series

Name	2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

Conference

Conference	7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023
Country/Territory	China
City	Hangzhou
Period	15/12/23 → 18/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

equivalent modeling
genetic algorithm
group division
K-means
wind farm

Access to Document

10.1109/EI259745.2023.10513132

Cite this

Yu, J., Huang, H., Xiao, Y., Ding, W., Li, J., & Liu, H. (2023). Dynamic Clustering and Operation Evaluation of Renewable Energy Station. In 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023 (pp. 4176-4181). (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EI259745.2023.10513132

Yu, Junsong ; Huang, Heyan ; Xiao, Yaohui et al. / Dynamic Clustering and Operation Evaluation of Renewable Energy Station. 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 4176-4181 (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023).

@inproceedings{ebcbabc3532141b5a1a652f4f44e60f7,

title = "Dynamic Clustering and Operation Evaluation of Renewable Energy Station",

abstract = "Aiming at the difference of dynamic characteristics about doubly-fed wind turbines and the complexity of equivalence problems, a multi-machine dynamic equivalence model for wind farms based on improved K-means algorithm is proposed. Considering the input wind speed and the different state parameters of the units, several indexes are selected to dynamically group the units in the wind farm. Based on the clustering results, the proposed wind farm's equivalent model is established in MATLAB/Simulink. According to the simulation results, the multi-machine equivalent model has higher accuracy and better application effect than the single-machine equivalent model, which can more effectively depict the grid-connected characteristics and operational state of doubly-fed wind farms.",

keywords = "equivalent modeling, genetic algorithm, group division, K-means, wind farm",

author = "Junsong Yu and Heyan Huang and Yaohui Xiao and Weifeng Ding and Jie Li and Hanxuan Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023 ; Conference date: 15-12-2023 Through 18-12-2023",

year = "2023",

doi = "10.1109/EI259745.2023.10513132",

language = "English",

series = "2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4176--4181",

booktitle = "2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023",

address = "United States",

}

Yu, J, Huang, H, Xiao, Y, Ding, W, Li, J & Liu, H 2023, Dynamic Clustering and Operation Evaluation of Renewable Energy Station. in 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023, Institute of Electrical and Electronics Engineers Inc., pp. 4176-4181, 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023, Hangzhou, China, 15/12/23. https://doi.org/10.1109/EI259745.2023.10513132

Dynamic Clustering and Operation Evaluation of Renewable Energy Station. / Yu, Junsong; Huang, Heyan; Xiao, Yaohui et al.
2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4176-4181 (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Dynamic Clustering and Operation Evaluation of Renewable Energy Station

AU - Yu, Junsong

AU - Huang, Heyan

AU - Xiao, Yaohui

AU - Ding, Weifeng

AU - Li, Jie

AU - Liu, Hanxuan

PY - 2023

Y1 - 2023

N2 - Aiming at the difference of dynamic characteristics about doubly-fed wind turbines and the complexity of equivalence problems, a multi-machine dynamic equivalence model for wind farms based on improved K-means algorithm is proposed. Considering the input wind speed and the different state parameters of the units, several indexes are selected to dynamically group the units in the wind farm. Based on the clustering results, the proposed wind farm's equivalent model is established in MATLAB/Simulink. According to the simulation results, the multi-machine equivalent model has higher accuracy and better application effect than the single-machine equivalent model, which can more effectively depict the grid-connected characteristics and operational state of doubly-fed wind farms.

AB - Aiming at the difference of dynamic characteristics about doubly-fed wind turbines and the complexity of equivalence problems, a multi-machine dynamic equivalence model for wind farms based on improved K-means algorithm is proposed. Considering the input wind speed and the different state parameters of the units, several indexes are selected to dynamically group the units in the wind farm. Based on the clustering results, the proposed wind farm's equivalent model is established in MATLAB/Simulink. According to the simulation results, the multi-machine equivalent model has higher accuracy and better application effect than the single-machine equivalent model, which can more effectively depict the grid-connected characteristics and operational state of doubly-fed wind farms.

KW - equivalent modeling

KW - genetic algorithm

KW - group division

KW - K-means

KW - wind farm

UR - https://www.scopus.com/pages/publications/85194156145

U2 - 10.1109/EI259745.2023.10513132

DO - 10.1109/EI259745.2023.10513132

M3 - Conference contribution

AN - SCOPUS:85194156145

T3 - 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

SP - 4176

EP - 4181

BT - 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

Y2 - 15 December 2023 through 18 December 2023

ER -

Yu J, Huang H, Xiao Y, Ding W, Li J, Liu H. Dynamic Clustering and Operation Evaluation of Renewable Energy Station. In 2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4176-4181. (2023 IEEE 7th Conference on Energy Internet and Energy System Integration, EI2 2023). doi: 10.1109/EI259745.2023.10513132

Dynamic Clustering and Operation Evaluation of Renewable Energy Station

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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