Aiming at the problems of complex calculation process, low efficiency and high energy consumption of the traditional energy metering multi-dimensional data clustering analysis algorithm, a set of suitable solutions is designed. The solution is based on a big data platform for calculation and storage, and multidimensional analysis of electric energy measurement data is carried out through the chaotic correlation dimension clustering analysis method. This method absorbs the advantages of traditional big data clustering algorithms and chaotic feature extraction, selectethe first minimum value of the interactive information as the best time delay and uses the false nearest neighbor algorithm to select the best embedding dimension u reconstruction phase space. Then,based on the phase space reconstruction, the chaotic correlation dimension characteristics are extracted and the clustering algorithmis combined to cluster the multi-dimensional data of electric energy measurement. Experiments prove that the chaotic correlation dimension clustering analysis method in this study is highly efficient,simple in process and low in energy consumption.