Harmonic pollution zoning method based on improved DBSCAN clustering

With the diversification of new energy power generation methods and the access of a large number of power electronic loads, the problem of harmonic pollution in the power grid tends to be more complicated and more diversified, making it more difficult to trace the location of harmonic sources. Starting from the engineering application of harmonic tracing and using power quality monitoring data, a method of harmonic zoning tracing based on density clustering is proposed. Based on the characteristics of harmonic measurement data, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), a time series clustering algorithm based on density is adopted. The method is based on a clustering concept which requires the number of objects contained in a certain area in the clustering space is not less than a given threshold, and the correlation information associated with harmonic pollution is mined. To improve the performance of the algorithm, K-Average Nearest Neighbor (K-ANN) algorithm and mathematical expectation method are introduced to solve the problem that the two important clustering parameters Eps and MinPts of this algorithm need to be manually set, and realize self-adaptation selection, thereby reducing the influence of human factors on the clustering results. The analysis shows that the proposed method can effectively realize the regional positioning of multi-harmonic sources. The position of the dominant harmonic source can be checked, and it is suitable for large-scale harmonic source access scenarios. Based on the data measured by the monitoring platform in a certain area, the practicability and effectiveness of the proposed method are verified.