Correlation Analysis of Wind Generator Wide Band Oscillation modes and influencing factors based on FP-Growth Method

Inhalt:
A FP-growth based correlation analysis method for wind generator oscillation modes and influencing factors is proposed in this paper. Primarily, by segmenting the collected data of wind turbine output power, voltage and wind speed, a method for mining and identifying oscillation modes based on Pony algorithm is proposed. Then by clustering the mean of wind speed and voltage based on spectral clustering algorithm, an association rule between wind speed - voltage clustering and oscillation modes based on FP - growth algorithm is proposed. Finally, based on the analysis of the results of association rule, an oscillation mode prediction method based on wind speed-voltage clustering is proposed. The proposed method in this paper can realize the oscillation mode identification of the unit based on the big data of wind turbine operation, which is of certain significance for improving the operation of wind turbine.