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- Title
基于聚类分析的风电场风速-出力典型 波动过程关联分析.
- Authors
程 林; 贾一超; 王吉利; 柯贤波; 韩华玲
- Abstract
In wind power generation system, studying the correlation characteristics between wind speed and power fluctuation can provide a good theoretical basis for wind power prediction, and has important reference value for enhancing the security and stability of power system. Aiming at the problem that power does not fluctuate linearly in real time with wind speed fluctuation, this paper has divided the wind speed and power fluctuation process by K-means clustering algorithm and fuzzy C-means clustering algorithm respectively, and obtained five different fluctuation processes. Then, the correlation characteristics of wind speed and power fluctuation under different fluctuation processes are analyzed by Pearson correlation analysis method and grey correlation analysis method. The results show that the maximum correlation coefficient is 0.4925 and the minimum correlation coefficient is 0.3318 in K-means clustering. In fuzzy C-means clustering, the maximum correlation coefficient is 0.4868 and the minimum correlation coefficient is 0.3293. Under all fluctuation processes, the grey correlation degree is around 0.5, indicating that the trend of power fluctuation is similar to that of wind speed fluctuation.
- Subjects
PEARSON correlation (Statistics); WIND speed; WIND power; FUZZY algorithms; STATISTICAL correlation; K-means clustering; FUZZY neural networks
- Publication
Journal of Xi'an Polytechnic University, 2022, Vol 36, Issue 5, p95
- ISSN
1674-649X
- Publication type
Article
- DOI
10.13338/j.issn.1674-649x.2022.05.013