Division of Multi-harmonic Responsibilities Based on DBSCAN Clustering and Interval Regression - Shilong CHEN; Tao WU; Cheng GUO; Zirui ZHANG; Jinghao SUN (Zhongguo dianli)
The traditional harmonic responsibility division methods are not applicable to the existing statistical harmonic monitoring data in the context of background harmonic impedance changes and background harmonic voltage fluctuations. Therefore, this paper proposes a multi-harmonic responsibility division method based on monitoring data under background harmonic changes. Firstly, a harmonic monitoring data interval sample set is constructed, and a mathematical model of multi-harmonic source interval harmonic responsibility division under background harmonic changes is established. Secondly, the collected statistical harmonic data set is clustered as the evaluation period by DBSCAN, and the data satisfying the linear relationship threshold requirement is screened by sliding window dynamic correlation analysis. Finally, the equation parameter and the optimal sample division scheme are obtained with the PM algorithm-based interval linear regression method, and the harmonic responsibility in the medium and long term time scope is calculated on the basis of the constructed interval harmonic responsibility division. The harmonic monitoring data of an actual power grid is used to verify the proposed method, and it is proved that the proposed method can use the existing statistical harmonic monitoring data to allocate the harmonic responsibility of each harmonic source in a reasonable time scale under background harmonic changes, which can provide new ideas for the division of responsibility for multiple harmonics during the operation of the actual power system.