Research on load curve clustering of distribution transformer based on wavelet transform and big data processing

It is very important to study the characteristics of the load curve of the distribution transformer for the low voltage transformation and transformer capacity of the distribution network. A clustering algorithm based on wavelet transform and big data processing method is proposed in this paper. The wavelet transform is applied to the feature extraction of the distribution load curve, and the clustering is improved by the improved quadratic clustering algorithm. It overcomes the shortcomings of traditional clustering convergence and sensitivity to the initial clustering center. By using the big data processing method in the Spark parallel processing framework to achieve the algorithm. Experiments show that the efficiency and accuracy of the algorithm are improved obviously.