@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",
}
