Aiming at the problem that the K-means algorithm needs to artificially specify the number of clustering in the process of power load data clustering

which leads to clustering result falling into the local minimum solution

a clustering method for power load data based on dynamic time warping（ DTW） histogram is presented.Principal component analysis（ PCA） method is used to reduce the dimension of high dimensional power load data.Histogram method is introduced to determine the initial clustering number of load data

the load curves are divided into K categories by DTW. The effectiveness of the method is verified on MATLAB simulation platform. The experimental results show that the proposed algorithm reduces the number of iterations in the operation process

accelerates the convergence speed of the algorithm

and achieves the effect of global optimal solution in the clustering analysis of power load data.